NSF Award
2424854
This project is a collaboration between three institutions: University of California-San Diego, Xavier University of Louisiana, and University of California-Irvine. The human blood contains different cell types that are continuously produced, while older cells die. As this process continues while the organism ages, mistakes are made during cell production, generating mutant cells. These mutants can linger in the blood and become more abundant over time. They can contribute to chronic health conditions and there is a chance that they initiate cancer. It is not well understood why these mutant cells persist and expand. One problem that has held back progress is that for obvious reasons it is impossible to perform experiments with human subjects to investigate this. Mathematics combined with epidemiological data, however, offers a way around this limitation. This project develops mathematical models describing the evolution of mutant cells in the blood over time, using experimental mouse data to define the model structure. New mathematical approaches are then used to adapt this model to the human blood system, by bridging between mathematical models of mutant evolution in the blood, and the epidemiological age-incidence of mutants in the human population. There is broad public health impact, since this work can suggest ways to reduce the mutant cells in patients, which can alleviate chronic health conditions and reduce cancer risk. From the educational perspective, the PIs collaborate with Xavier University of Louisiana, an undergraduate historically black university, to foster enthusiasm in continued education and careers in STEM, and equip students with knowledge and skills to potentially continue in graduate programs at top universities, thus promoting social mobility.<br/><br/>As higher organisms age, tissue cells acquire mutations that can rise in frequency over time. Such clonal evolutionary processes have been documented in many human tissues and have become a major focus for understanding the biology of aging. Gaining more insights into mechanisms that drive mutant emergence in non-malignant human tissues is an important biological / public health question that needs to be addressed to define correlates of tissue aging. While experiments in mice have suggested possible drivers of mutant evolution in tissues, a central unresolved question is whether (and how) knowledge from murine models can be applied to humans. Mathematics provides a new approach to address this challenge: We propose a multiscale approach that uses mathematics to bridge between cellular dynamics of mice and humans, by utilizing epidemiological data of mutant incidence in human populations. We use “clonal hematopoiesis of indeterminate potential” (CHIP) as a study system, where TET2 and DNMT3A mutant clones emerge in the histologically normal hematopoietic system. Based on stem cell transplantation experiments in mice, we seek to construct a predictive mathematical model of mutant evolution in mice. Using the hazard function, this in vivo model can predict the epidemiological incidence of mutants. Fitting predicted to observed mutant age-incidence data for humans will yield a parameterized and predictive model of human TET2 and DNMT3A mutant evolution. Public health impacts include a better understanding of mutant evolution in the human hematopoietic system, which may lead to evolution-based intervention strategies to reduce CHIP mutant burden.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
