The landscape of clonal mosaicism of the blood in individuals with Down Syndrome

About This Grant

PROJECT SUMMARY Aging impacts many functions within cells, from genomic instability to oxidative damage to shifted cellular metabolism. Similarly, collections of cells change in their relative composition with age—a phenomenon mainly driven by clonal selection; this process has been extensively studied in the hematopoietic system, where a clear correlation between clonality changes and age has been described. While these changes are sometimes precursors to blood malignancies, they are much more commonly observed in their absence and have been correlated with changes in inflammation status, as well as cardiovascular, liver, and Alzheimer’s disease. Counterintuitively, this so-called ‘clonal hematopoiesis of indeterminate potential’ (CHIP) has been associated with both adverse and beneficial outcomes, suggesting a currently unresolved dichotomy. Individuals with Down syndrome (DS) exhibit global changes in immune activation and altered hematopoiesis that frequently result in transient preleukemia and elevated leukemia risk. Connecting clonal hematopoiesis to hematological malignancies, increased levels of CHIP have been observed in individuals with DS; critically, the frequency is both increased and significantly earlier in life than expected. One limitation of current CHIP analysis is its phenotype based on the presence or absence of known driver mutations or large-scale structural variants. However, changes in clonality may presage or be independent of CHIP and are available through the genome-wide detection of ‘neutral’ mosaic variants. Thus, we hypothesize that clonal mosaicism of the hematopoietic system (CM-HS) represents a quantitative trait with increased sensitivity to detect blood clonality alterations for individuals with DS. To test this hypothesis and implement this framework, we plan to leverage local resources through the Linda Crnic Institute, which harbors a biobank of samples from individuals with DS with matched genome sequencing data through the Gabriella Miller Kids First (GMKF) program. We will first analyze ~450 readily available 60× coverage whole- genome data sets employing our novel approaches for mosaicism detection. Our team also has access to detailed clinical and multi-omics data; this will allow the correlation of CM-HS with clinical and functional phenotypes and establish a biosignature of blood clonality changes in DS (Aim 1). Subsequently, we will migrate our bioinformatic toolkit to the CAVATICA platform to perform analyses across the available Down syndrome data (~1,700 cases) and matched controls through GMKF (Aim 2). Together, these analyses will provide novel insight into blood clonality changes in DS through CM-HS detection. Based on our expectations and preliminary data, we expect that CM-HS can reflect and possibly predict alterations in the hematopoietic system—be it through inflammation or stem cell selection. The work proposed here will allow us to develop the analytical framework for CM-HS analysis, employ it across a deeply phenotyped smaller cohort to determine associations, as well as a population-scale cohort.