Cost-Effective and Scalable Clonal Hematopoiesis Assay Provides Insight into Clonal Dynamics.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related phenomenon in which hematopoietic stem cells acquire mutations in a select set of genes commonly mutated in myeloid neoplasia which then expand clonally. Current sequencing assays to detect CHIP mutations are not optimized for the detection of these variants and can be cost-prohibitive when applied to large cohorts or to serial sequencing. In this study, an affordable (approximately US $8 per sample), accurate, and scalable sequencing assay for CHIP is introduced and validated.

Cost-effective and scalable clonal hematopoiesis assay provides insight into clonal dynamics.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related phenomenon that occurs when hematopoietic stem cells acquire mutations in a select set of genes commonly mutated in myeloid neoplasia which then expand clonally. Current sequencing assays to detect CHIP are not optimized for the detection of these variants and can be cost-prohibitive when applied to large cohorts or serial sequencing. Here, we present and validate a CHIP targeted sequencing assay that is affordable (∼$8/sample), accurate and highly scalable.

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis.

Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R ~ 83-97%).

Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program.

All of Us is a biorepository aiming to advance biomedical research by providing various types of data in diverse human populations. Here we present a demonstration project validating the program's genomic data in 98,622 participants. We sought to replicate known genetic associations for three diseases (atrial fibrillation [AF], coronary artery disease, type 2 diabetes [T2D]) and two quantitative traits (height and low-density lipoprotein [LDL]) by conducting common and rare variant analyses.