Technological validation of error-corrected sequencing of CHIP genes

As we age, our blood stem cells can acquire mutations in genes typically involved in cancer, but without being cancerous. This phenomenon is called clonal hematopoiesis of indeterminate potential (CHIP). Although these mutations are not directly cancerous, research indicates that individuals with CHIP face an elevated risk of certain diseases, including hematological cancers and cardiovascular diseases. So far, the study of clonal hematopoiesis has largely been limited to mutations above the variant allele frequency (VAF) threshold of 2% due to the technological limitations of whole exome sequencing, the most commonly used technology for CHIP. As the depth of sequencing is typically at 50 sequences of read depth (50x), this limits the detection of clonal mutations to 2% with low precision. As such, the health consequences of smaller clones remain largely understudied. The study of Van Zeventer et al. (2023, doi: 10.1016/j.ccell.2023.04.006) used error-corrected sequencing at high read depth (>8000 x) in 7,045 DNA samples from 3,359 participants in the population-based Lifelines cohort. The study showed that a majority of the smaller clones grew to reach VAF > 2% over time, emphasizing the importance of studying mutations of low clonal size. 
At the Pharmacogenomics Centre of the Montreal Heart Institute, we have developed an error-corrected deep sequencing pipeline to detect mutations in CHIP genes at high sequencing depth. We designed a custom targeted amplification panel (Paragon) of 11 selected genes involved in CHIP (ASXL1, CBL, DNMT3A, GNAS, GNB1, JAK2, PPM1D, SF3B1, SRSF2, TET2 and TP53). Libraries are prepared with primers labelled with unique molecular indexes (UMI) and Unique Dual Indexes (UDI), and we perform paired-end sequencing on a NovaSeq 6000 instrument, with median coverage depth of 35,000x (900x post UMI processing). We have implemented a bioinformatics pipeline according to Paragon's guidelines specific to the CleanPlex custom panel. We use the bioinformatics tools fgbio and verdict, and CHIP mutations are annotated using Annovar and VEP. To filter somatic mutations, we rely on the use of a whitelist of selected variants as presented by Jaiswal et al. 2017 (doi: 10.1056/NEJMoa1701719) and Bick et al. 2020 (TOPMed) (doi: 10.1038/s41586-020-2819-2). 
Here, we would like to request access to the processed somatic variant calls from the Lifelines-CH study by Van Zeventer et al. which is made available within the European Genome-Phenome Archive. We would like to use the somatic variant calls from the Lifelines cohort solely to assist in the technological validation of our error-corrected sequencing, at the filtering step of our pipeline. No conclusion will be directly drawn from the Lifelines cohort and it will not be used otherwise. The Lifelines processed somatic variant calls will support our assessment of detected mutations that are more likely the result of technological noise. Such technological validation will help us refine our analyses of CHIP variants, and increase the reliability and generalizability of the findings based on our developed pipeline.
All data accessed will be used strictly for research purposes, adhering to the data ethics, confidentiality, and security protocols established at the Montreal Heart Institute. This project is funded in part by the Canadian Institutes of Health Research (CIHR) under grant application number 409752.