MRC Human Genetics Unit
Medical Research Council Human Genetics Unit

Which molecular mechanisms underlie age-dependent disease risk?

Advanced age is the most significant risk factor for neurodegenerative, cardiovascular and malignant diseases. Why age predisposes to disease risk and how is poorly understood. What are the molecular mechanisms underlying age-dependent disease risk, and can we delay them?

Recent models estimate that delaying ageing by targeting an underlying common process, could solve the problem of competing risks and have an economic value of $7.1 trillion over 50 years (1).

1.Goldman, D. The economic promise of delayed aging. Cold Spring Harb. Perspect. Med. 6, (2016).

Topic 1: How does cellular senescence contribute to human ageing and disease? 

Which molecular mechanisms underlie age-dependent disease risk?

Over the last decade, we have made important contributions to the mechanistic and molecular understanding of the complex changes leading to cellular senescence. These include the role of chromatin changes in cellular senescence and Progeria and the interaction of senescent cells with their environment. While we continue our pursuit in understanding the basic mechanisms behind cellular senescence, there is one question that hinders translation of this knowledge:

How does cellular senescence contribute to human ageing and disease?

This is the important question that we wish to address over the next years. It is timely because research into candidate senolytics and clinical trials are rapidly intensifying, triggered by observed benefits to prematurely ageing mice upon clearance of senescence cells. If senolytics can deliver therapeutic benefit, it is essential that we perform trials on them only for those human diseases, including cancer, whose aetiology includes senescence.

Replicative senescence is the finite capability of cells to proliferate in culture and may offer a cellular model with which to study organismal ageing. Additional cellular models of ageing exist, such as cells from either progeroid syndromes or old individuals, and cells in which senescence has been induced by oncogene activation or high levels of DNA damage.

The area of senescence has recently been energised by observations, in mouse, that clearance of senescent cells (senolysis) leads to improved health outcomes and an extension of a healthy lifespan. The field hypothesises that senescence has a critical role in mediating the complex process of ageing in humans and its associated pathologies. Early results of senolytic studies of premature ageing phenotypes were promising, leading to investigations of acute pancreatitis, lung fibrosis and type-2 diabetes. 

Nevertheless, directly implicating senescence in human disease has proved a major challenge, because to date most evidence has emerged from cell culture or mouse models. Manipulating cellular senescence to prevent or ameliorate disease has potential, as indicated by a growing number of senolytics companies and by multiple proof-of-concept clinical trials using senolytic drugs that target senescent cells. However, an aetiological understanding of the links between cellular phenotype and organismal phenotype is lacking, resulting in a lack of evidence of where and how senolytics should be targeted.

We aim to bridge the gap of molecular understanding and human disease by generating senescence-specific molecular signatures and the use of genetics to identify senescence driven human traits. We are working to integrate large cohort and molecular data.



  • Kirschner, K., Rattanavirotkul, N., Quince, M. F. & Chandra, T. Functional heterogeneity in senescence. Biochemical Society Transactions 48,765–773 (2020).
  • Rattanavirotkul, N., Kirschner, K. & Chandra, T. Induction and transmission of oncogene-induced senescence. Cellular and Molecular Life Sciences,1–10 (2020). 
  • Chiang, M., Michieletto, D., Brackley, C. A., Rattanavirotkul, N., Mohammed, H., Marenduzzo, D.& Chandra, T. Polymer modeling predicts chromosome reorganization in senescence. Cell reports 28,3212–3223 (2019).
  • Teo, Y. V., Rattanavirotkul, N., Olova, N., Salzano, A., Quintanilla, A., Tarrats, N., Kiourtis, C.,Müller, M., Green, A. R., Adams, P. D.,et al. Notch signaling mediates secondary senescence.Cell reports 27,997–1007 (2019).
  • Pantazi, A., Quintanilla, A., Hari, P., Tarrats, N., Parasyraki, E., Dix, F. L., Patel, J., Chandra,T., Acosta, J. C. & Finch, A. J. Inhibition of the 60S ribosome biogenesis GTPase LSG1 causes endoplasmic reticular disruption and cellular senescence.Aging cell18,e12981 (2019).
  • Aarts, M., Georgilis, A., Beniazza, M., Beolchi, P., Banito, A., Carroll, T., Kulisic, M., Kaemena, D. F.,Dharmalingam, G., Martin, N.,et al. Coupling shRNA screens with single-cell RNA-seq identifies a dual role for mTOR in reprogramming-induced senescence. Genes & development 31,2085–2098(2017). 
  • Chandra, T. The Functional Nucleus 205–218 (Springer, Cham, 2016).
  • Chandra, T. & Kirschner, K. Chromosome organisation during ageing and senescence.Current opinion in cell biology 40,161–167 (2016)
  • Chandra, T., Ewels, P. A., Schoenfelder, S., Furlan-Magaril, M., Wingett, S. W., Kirschner, K.,Thuret, J.-Y., Andrews, S., Fraser, P. & Reik, W. Global reorganization of the nuclear landscape in senescent cells.Cell reports 10,471–483 (2015).
  • Sadaie, M., Salama, R., Carroll, T., Tomimatsu, K., Chandra, T., Young, A. R., Narita, M., Pérez-Mancera, P. A., Bennett, D. C., Chong, H.,et al.Redistribution of the Lamin B1 genomic binding profile affects rearrangement of heterochromatic domains and SAHF formation during senescence.Genes & development 27,1800–1808 (2013).
  • Chandra, T., Kirschner, K., Thuret, J.-Y., Pope, B. D., Ryba, T., Newman, S., Ahmed, K., Samarajiwa,S. A., Salama, R., Carroll, T.,et al.Independence of repressive histone marks and chromatin compaction during senescent heterochromatic layer formation. Molecular cell 47,203–214 (2012).
  • Hirosue, A., Ishihara, K., Tokunaga, K., Watanabe, T., Saitoh, N., Nakamoto, M., Chandra, T.,Narita, M., Shinohara, M. & Nakao, M. Quantitative assessment of higher-order chromatin structure of the INK4/ARF locus in human senescent cells. Aging cell11,553–556 (2012).

Topic 2: Somatic mosaicism in ageing and cancer (With Kirschner, Schumacher and Marioni labs. Supported by LBC, GS and UK Biobank)

Dynamics of age-related clonal haematopoiesis

Age-related clonal haematopoiesis (ARCH) is apparent in the general population from age 60 with a steady increase to 18-20% over age 90 driven by somatic mutations in leukaemic driver genes, leading to reduced diversity of the blood pool. ARCH carries an increased risk for leukaemia, cardiovascular disease and ischemic heart failure. Through data generation and annotation of two existing unique cohorts of aged individuals, the Lothian birth cohorts (LBC) 1921 and 1936, we aim to establish a direct link between age-related morbidities in relation to ARCH. Our own work showed that ARCH mutations may contribute to premature ageing. We found an increase in epigenetic age – a measure of biological rather than chronological age – for 73 participants with ARCH from the LBCs.

Classifying human stem cell fitness of pre-leukaemic mutations to inform progression to malignancy (With Kirschner and Schumacher labs)

ARCH is associated with an estimated 10-fold increased risk for developing a haematological neoplasm. Our mechanistic understanding of how specific ARCH variants drive clonal expansion and transformation to cancer is limited. Since mutations in stem cells often drive leukaemia, we hypothesise that stem cell fitness substantially contributes to the transformation from ARCH to leukaemia. Stem cell fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. This project will enable stratification of individuals with harmful ARCH variants that merit close clinical management for early detection or prevention of leukaemia, and generate new biological insight into how different variants increase stem cell fitness.

Causes and consequences of ARCH (With Marioni lab)

Taking advantage of the longitudinal life-course data from the two independent cohorts LBC1921 and LBC1936, Generation Scotland and other cohorts we will test and validate associations between ARCH status in later life and the following factors: Lifestyle and deprivation (e.g. smoking, alcohol intake, dietary patterns, socioeconomic position across the lifespan), cognitive data, genetics (GWAS of ARCH and its relation to polygenic risk scores, annotation of cis quantitative trait loci (QTL)/transQTL), non-blood-related diseases (e.g. hypertension, cardiovascular disease, breast/prostate cancer – disease outcomes will be assessed via data linkage to electronic health records), physical ageing (e.g. longitudinal change in lung function, grip strength, walking speed), brain ageing (3 time points of 3T MRI in LBC1936 for ~500 participants) and dementia.

Functional consequences of ARCH mutations in single HSPCs (With Kirschner lab)

To address the mechanisms by which ageing contributes to clonal haematopoiesis, we explore the effects of ARCH mutations on clonal distribution and molecular and cellular properties of aged HSPCs. We are using combinations of single-cell genomics and stem-cell assays in human and mouse samples.

The role of methylation in ARCH

Given that ARCH mutations are commonly found in genes responsible for de novo DNA methylation, we will combine the existing longitudinal blood-based DNA methylation (DNAm) from LBCs with the newly collected longitudinal ARCH data to explore their relationship.



  • Terradas-Terradas, M., Robertson, N. A., Chandra, T. & Kirschner, K. Clonality in haematopoietic stem cell ageing. Mechanisms of Ageing and Development 189,111279 (2020).
  • Robertson, N. A., Hillary, R. F., McCartney, D. L., Terradas-Terradas, M., Higham, J., Sproul, D.,Deary, I. J., Kirschner, K., Marioni, R. E. & Chandra, T. Age-related clonal haemopoiesis is associated with increased epigenetic age. Current Biology 29, R786–R787 (2019).
  • Kirschner, K., Chandra, T., Kiselev, V., Flores-Santa Cruz, D., Macaulay, I. C., Park, H. J., Li, J.,Kent, D. G., Kumar, R., Pask, D. C.,et al. Proliferation drives aging-related functional decline in a subpopulation of the hematopoietic stem cell compartment. Cell reports 19,1503–1511 (2017).

Topic 3: Epigenetic age and epigenetic rejuvenation 

Epigenetic age and epigenetic rejuvenation

Epigenetic age is a predictor of biological age

The recent generation of predictors that accurately predict biological age has led to a new, quantitative era in molecular ageing research. Epigenetic ageing clocks predict chronological age based on the hyper-or hypomethylation of specific CpGs, which correlate strongly with age (Fig.1). Significant associations with known age-accelerating conditions, such as Werner syndrome, Down’s syndrome patients, HIV therapy and many others, have confirmed that epigenetic age is a quantitative measurement for biological age.

Epigenetic age reversal is possible

In 2016, it was shown that in mice, the reversal of age-related phenotypes is possible through transient short pulse expression of Yamanaka factors (reprogramming factors)17. Our work showed that adult human cells treated with reprogramming factors undergo a rejuvenation phase by decreasing their epigenetic age without dedifferentiating. This is an important distinction, as dedifferentiation bears the risk of cancer. Our observations have now been confirmed by several labs, including in mice by Prof Reik’s lab in Cambridge.

We are actively working on (i) improving current methods of epigenetic age prediction, and their (ii) biological interpretation. We also continue our study on finding drivers and rejuvenating approaches of epigenetic age. 

Olova, N., Simpson, D. J., Marioni, R. E. & Chandra, T. Partial reprogramming induces a steady decline in epigenetic age before loss of somatic identity. Aging cell 18,e12877 (2019).

Simpson, D. J. & Chandra, T. Epigenetic age prediction. Aging cell under review (2021).

McCartney, D. L., Zhang, F., Hillary, R. F., Zhang, Q., Stevenson, A. J., Walker, R. M., Bermingham,M. L., Boutin, T., Morris, S. W., Campbell, A.,et al. An epigenome-wide association study ofsex-specific chronological ageing. Genome medicine 12,1–11 (2020).