Publications

A scalable multimodal framework for unbiased risk biomarker discovery across multiple cancer types(opens in a new tab)

Constantin Petrescu · Jack Monahan · Abbas Salami · Lisa Schmunk · Tom Stubbs, PhD

Cancer Research 86 (7_Supplement): Abstract 1116 · 2026 · aacrjournals.org

A novel framework to build saliva-based DNA methylation biomarkers: quantifying systemic chronic inflammation as a case study(opens in a new tab)

Lisa Schmunk · Toby Call · Hira Javaid · Vanja Jovicevic · Drago Kojadinovic · Natacha Tomkinson · Emma Stone · Milos Gavrilov · Rob Thompson · Tom Stubbs, PhD · Dani Martin-Herranz, PhD — with Daniel L McCartney, Waylon J Hastings, Eliska Zlamalova, Kirsty C McGee, Jack Sullivan, Archie Campbell, Andrew M McIntosh, Veronika Óvári, Karl Wishart, Christian E Behrens, Thomas Jackson, Janet M Lord

Accessible and non-invasive biomarkers that measure human ageing processes and the risk of developing age-related disease are paramount in preventative healthcare. Here, we describe a novel framework to train saliva-based DNA methylation (DNAm) biomarkers that are reproducible and biologically interpretable. By leveraging a reliability dataset with replicates across tissues, we demonstrate that it is possible to transfer knowledge from blood DNAm to saliva DNAm data using DNAm proxies of blood proteins (EpiScores). We apply these methods to create a new saliva-based epigenetic clock (InflammAge) that quantifies systemic chronic inflammation (SCI) in humans. Using a large blood DNAm human cohort with linked electronic health records and over 18,000 individuals (Generation Scotland), we demonstrate that InflammAge significantly associates with all-cause mortality, disease outcomes, lifestyle factors, and immunosenescence; in many cases outperforming the widely used SCI biomarker C-reactive protein (CRP). We propose that our biomarker discovery framework and InflammAge will be useful to improve understanding of the molecular mechanisms underpinning human ageing and to assess the impact of gero-protective interventions.

2025 · bioRxiv

Genomic discovery and functional validation of MRP1 as a novel fetal hemoglobin modulator and potential therapeutic target in sickle cell disease(opens in a new tab)

Lisa Schmunk — with Yannis Hara, Emily Kawabata, Viktor T Lemgart, Paola G Bronson, Alexandra Hicks, Robert Peters, Sriram Krishnamoorthy, Jean-Antoine Ribeil, Jennifer Eglinton, Nicholas A Watkins, David J Roberts, Emanuele Di Angelantonio, John Danesh, William J Astle, Dirk S Paul, Samuel Lessard, Adam S Butterworth

ABSTRACT Sickle cell disease (SCD) remains a major health burden with limited treatment options. Despite promising gene-editing clinical trials, there is an unmet need for cost-effective therapies. As induction of fetal hemoglobin (HbF) is an established therapeutic strategy for SCD, we conducted a genome-wide association study of circulating HbF levels in ~11,000 participants to identify further HbF modulators. We identified associations in 11 genomic regions, including eight novel loci such as ABCC1 (encoding multidrug resistance-associated protein 1, MRP1). Using gene-editing and pharmacological approaches, we showed that inhibition of MRP1 increases HbF, intracellular glutathione levels, and reduces sickling in erythroid cells from SCD patients. Overall, our findings identify several novel genetically-validated potential therapeutic targets for SCD, including promising proof-of-principle results from small molecule inhibition of MRP1.

2023 · medrxiv.org

Single cell DNA methylation ageing in mouse blood(opens in a new tab)

Tom Stubbs, PhD

ABSTRACT Ageing is the accumulation of changes and overall decline of the function of cells, organs and organisms over time. At the molecular and cellular level, the concept of biological age has been established and biomarkers of biological age have been identified, notably epigenetic DNA-methylation based clocks. With the emergence of single-cell DNA methylation profiling methods, the possibility to study biological age of individual cells has been proposed, and a first proof-of-concept study, based on limited single cell datasets mostly from early developmental origin, indicated the feasibility and relevance of this approach to better understand organismal changes and cellular ageing heterogeneity. Here we generated a large single-cell DNA methylation and matched transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages (10-101 weeks of age). We observed that the number of genes expressed increased at older ages, but gene specific changes were small. We next developed a robust single cell DNA methylation age predictor (scEpiAge), which can accurately predict age in a broad range of publicly available datasets, including very sparse data and it also predicts age in single cells. Interestingly, the DNA methylation age distribution is wider than technically expected in 19% of single cells, suggesting that epigenetic age heterogeneity is present in vivo and may relate to functional differences between cells. In addition, we observe differences in epigenetic ageing between the major blood cell types. Our work provides a foundation for better single-cell and sparse data epigenetic age predictors and highlights the significance of cellular heterogeneity during ageing. Highlights - Model to estimate DNA methylation age in single cells - Large multi-omics dataset of single cells from murine blood - Epigenetic age deviations from chronological age are greater than technical expected from technical variability - Number of genes expressed increases with chronological and epigenetic age

bioRxiv (preprint) · 2023 · doi.org/10.1101/2023.01.30.526343

Screening for genes that accelerate the epigenetic ageing clock in humans reveals a role for the H3K36 methyltransferase NSD1(opens in a new tab)

Dani Martin-Herranz, PhD · Tom Stubbs, PhD

ABSTRACT Background Epigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data, and which have emerged in the last few years as the most accurate biomarkers of the ageing process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harbouring mutations in proteins of the epigenetic machinery. Results Using the Horvath epigenetic clock, we performed an unbiased screen for epigenetic age acceleration (EAA) in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic ageing. Furthermore, we show that the normal ageing process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterised by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients. Conclusions These results suggest that the H3K36 methylation machinery is a key component of the epigenetic maintenance system in humans, which controls the rate of epigenetic ageing, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic ageing clock and we expect will shed light on the different processes that erode the human epigenetic landscape during ageing.

bioRxiv (preprint) · 2019 · doi.org/10.1101/545830