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This work is published and available within Brown et al. (2020). Our work evaluates the relationship between telomere length and the presence of clonal somatic copy number alterations (SCNAs). We inferred telomere length for 431,501 subjects within the UK Biobank using a polygenic risk score (PRS) of variants previously associated with leukocyte telomere length. Genotyping array data were also acquired and used to detect SCNAs in the same population. Overall, we demonstrated a positive association between the telomere length PRS and the presence of autosomal SCNAs. The SCNAs call set (as detailed within Loh et al. (2020)) has also been returned to UK Biobank (as Return 2062) to enable individual-level linkage to approved UK Biobank applications. This research was conducted under the UK Biobank applications 19808 and 21552.
Detection of large-scale copy-number and copy-neutral mosaic alterations in circulating leukocyte DNA of UK Biobank cancer cases and cancer-free controls
We aim to investigate potential differences in frequency and location of large acquired copy number mutations in blood derived DNA of cancer cases and healthy controls. Our past research has demonstrated that the frequency of large, mosaic mutations increases with age, but has produced limited evidence for cancer associations. The UK Biobank is a well-powered collection of samples with the opportunity to provide new insights into how large acquired copy number mutations in the blood may be related to future cancer risk as well as perform a genome-wide association study of mosaic copy number alterations. Our proposed research compliments UK Biobank's aim of improving the prediction and detection of serious and life-threatening illnesses such as cancer by investigating how an individual's acquired copy number mutations may relate to their future risk of cancer. Our calling algorithms will scan the chromosomes of all UK Biobank participants with genotyping data to detect large, acquired mosaic events. Frequencies and locations of events will be compared across individual characteristics in univariate and multivariate models to better understand how acquired copy-number and copy-neutral events relate to cancer risk. We propose to use all participants from the full cohort with available SNP array genotyping data.