Systematic Evaluation of Somatic Contamination in Germline Genomes

Large-scale genomic initiatives like the UK Biobank (UKB) have revolutionized our understanding of human disease. These studies typically assume that blood-derived DNA faithfully reflects an individual’s germline genome. However, this assumption is challenged by somatic mutations arising from processes like clonal hematopoiesis. Although standard bioinformatics pipelines employ variant allele frequency (VAF)-based filtering to mitigate such contamination, the efficacy of these approaches requires systematic evaluation. By systematically analyzing whole-exome sequencing (WES) and whole-genome sequencing (WGS) data from large cohorts, including the UK Biobank, The Cancer Genome Atlas (TCGA), and the 1000 Genomes Project, we revealed critical limitations in current filtering methodologies. We found that the mutational spectrum of rare “germline” variants is highly similar to that of somatic mutations. Furthermore, we uncovered these variants show significant associations with phenotypes such as age, sex, and smoking status, established drivers of somatic mutagenesis. This persistent somatic contamination introduces substantial confounder effects, potentially generating spurious associations and reverse causality in genetic studies. Our work underscores the urgent reconsideration of two fundamental aspects of genomic research: (1) refinement of variant filtering strategies to better distinguish true germline variants from somatic contaminants, and (2) incorporation of somatic mutagenesis factors as essential covariates in study design. Our findings provide a basic framework for improving the accuracy and interpretability of large-scale genomic studies.