Kali Quade, “Characterizing mCAs by Age, Sex, Ancestry, and Genomic Location to Predict Hematologic Malignancy”
Mentor: Paul Auer, MCW (partnership with UWM)
Poster #149
Hematopoietic stem cells are precursors for all blood cell types, which, during the maturation process, may accumulate genetic mutations. While many of these mutations have minimal impact, some confer a competitive advantage, leading to the formation of large colonies—a phenomenon known as clonal hematopoiesis. This process has been linked to several diseases, including heart disease, arteriosclerosis, and hematologic malignancies. Notably, by the age of seventy, approximately 10% of the healthy U.S. population exhibits clonal hematopoiesis, with prevalence escalating with age. One significant mutation type contributing to clonal hematopoiesis is mosaic chromosomal alterations (mCAs), where substantial portions of somatic DNA undergo alterations. Importantly, certain mCAs have an increased association with the development of hematologic malignancies, and their prevalence varies across demographic groups. To explore these relationships, we utilized the All of Us database, which offers comprehensive health records from a diverse set of individuals which previous studies often lack. We found that frequencies and chromosomal locations of autosomal mCAs differ based on age, sex, and ancestry, with implications for predicting both hematologic and non-hematologic malignancies. This conclusion came after we analyzed mCA frequencies across individuals of varying demographics, identified chromosomal loci harboring the most mCAs within these groups, and finally, assessed whether the identified mCAs can predict the onset of blood cancers. Recent findings found across four large-scale biobanks include identification of novel risk loci that modulate mCA risk, associations with other diseases with emphasis blood cell count abnormalities. Future analysis involves characterizing and finding associations between blood pressure and mCAs in the UK Biobank. By uncovering demographic-specific patterns of mCAs, we aim to tailor personalized cancer prevention and treatment strategies, recognizing the diverse genetic variability underlying hematologic malignancies.