Mutational signatures in the general population

Abstract

Mutational processes leave characteristic patterns of somatic mutations, traditionally studied in tumour tissue. Far less is known about whether they can be observed in normal tissue, particularly blood. Detecting the mutational imprint of disease-associated processes there could enable earlier detection and intervention. Here, we investigate whether the mutational signal detected in blood can be explained by biological and clinical factors, in particular age, DNA repair deficiencies, and cancer diagnoses. Using whole-genome sequencing of blood-derived DNA from 17,419 UK Biobank participants, we developed a filtering strategy to isolate somatic mutations and analysed four views of the mutational landscape: mutation burden, mutation channel composition, exposures to de novo signatures and exposures to COSMIC signatures. We modelled their relation to these factors using regression analysis. Across all four views, sequencing provider was the dominant predictor, far outweighing other predictors. Among non-technical predictors, BRCA (p = 0.024) and POLE (p = 0.030) variants were significantly associated with a higher mutation burden. A leukaemia diagnosis was the strongest signal across the remaining views, appearing in both the mutation channel composition and the exposure to the clock-like signature SBS1 (p = 2.10e-06). De novo signature exposures clustered by sequencing provider, and no association survived when extraction was performed separately for each provider. Our results show that some biological and clinical factors do explain part of the mutational signal in blood, but that technical variation between sequencing providers dominates the mutational landscape and must be addressed before blood can serve as a reliable substrate for mutational analysis.