Research Line 1: Clonal Hematopoiesis of Indeterminate Potential (CHIP)

Clonal hematopoiesis of indeterminate potential (CHIP) is a pre-malignant state characterized by the accumulation of somatic mutations in hematopoietic stem cells (HSCs) and the expansion of genetic clones in blood. CHIP correlates with increased risk of hematological malignancies and cardiovascular diseases. However, conventional population-level analyses fail to account for inter-individual variations in clonal composition and mutation progression, limiting our ability to predict which individuals will progress to disease.
In this research line, we combine targeted error-corrected sequencing with mathematical modeling to track, in vivo, the longitudinal evolution of mutations at pre-clinical stages. By exploiting longitudinal dynamics, we aim to distinguish fitness-inducing mutations from neutral drift, resolve clonal hierarchies—determining whether mutations co-occur within the same HSCs or compete across different clones—and quantify how individual-specific bone marrow microenvironments modulate clonal expansion (Robertson et al., 2022, Nature Medicine; Latorre-Crespo et al., 2025, BioRxiv). More precisely, we seek to understand how mutation timing, fitness, and clonal structure interact to determine clinical progression and to produce novel biomarkers of mortality progression. For this, we closely collaborate with clinicians to develop strategies for risk stratification and follow-up guidelines in individuals presenting CHIP and therapy-related CHIP (Badar et al., 2025, Blood Advances).
 

Research Line 2: Epigenetic Aging – A Cellular Mechanics Perspective

Epigenetic aging has emerged as the most reliable quantitative biomarker of biological age, showing strong associations with diverse phenotypes and diseases. However, while epigenetic clocks successfully assess aging speed across tissues and species, the fundamental processes driving aging speed have remained poorly understood.

In this research line, we develop cellular mechanisms-informed mathematical models of epigenetic aging, conceptualizing age-related methylation changes as stochastic shifts occurring during cell replication. This approach aims to provide mechanistic interpretability to epigenetic clocks by decomposing epigenetic aging rate into stem cell replication rate and methylation change probability per division (Dabrowski et al., 2024, Nature Aging). By testing whether differences in epigenetic aging rates across species reflect differences in stem cell dynamics, we discovered scaling laws linking DNA methylation rates to maximum lifespan across mammals, mirroring patterns observed for somatic mutations and telomere shortening (Crofts, Latorre-Crespo & Chandra, 2023, Nature Aging). Whether stem cell replication serves as an upstream regulator unifying multiple hallmarks of aging and its role in determining accelerations in epigenetic aging or the lifespan of species remains an open question which forms the basis of our research.