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Approved research

Identifying the regulators of clonal hematopoiesis of indeterminate potential (CHIP)

Principal Investigator: Professor Benjamin Ebert
Approved Research ID: 50834
Approval date: November 8th 2019

Lay summary

Clonal hematopoiesis of indeterminate potential (CHIP) is a common condition among the elderly where a substantial proportion of mature blood cells develop from a single dominant stem cell lineage. It is detected by the presence of somatic mutations in blood cells. While CHIP is considered a consequence of normal aging, CHIP associates with increased mortality and risk for hematologic and cardiovascular phenotypes. A number of candidate genes mutated in CHIP have been identified which are also frequently mutated in blood cancer (e.g., DNMT3A, ASXL1, TET2, JAK2, SF3B1, TP53, PPM1D, and others). However, the mechanisms underlying CHIP and factors influencing CHIP development and progression to phenotypic outcomes remain unknown. We aim to identify genetic and non-genetic regulators of clonal expansion of blood cells and disease outcomes in CHIP cases. We will investigate the influence of inborn genetic variations on CHIP. To date, predisposition for CHIP has only been investigated in the Icelandic population, and only one risk locus has been identified (TERT). Performing association study in a large number of samples can reveal novel risk variants that predispose for CHIP. To identify potential phenotypic outcomes of CHIP, we will investigate the association of CHIP with clinical phenotypes and demographic features. Charting the phenotypic landscape of CHIP is crucial to understand the mechanisms underlying CHIP. We will utilize the richly annotated clinical features in the UK Biobank to identify potential phenotypic outcomes of CHIP. This project will run for 12 months and identify novel germline regulators of CHIP development and potential phenotypic outcomes. The results will expand our understanding of the mechanisms underlying CHIP and open avenues for future research. From a practical viewpoint, our analysis will potentially reveal predictors of CHIP and phenotypic outcomes which may enable stratification of CHIP cases, and facilitate risk prediction both in affected individuals and in relatives.