• National Cancer Institute, Rockville, MD, United States.
• National Cancer Institute, Bethesda, United States.
• Washington University in St. Louis, St. Louis, United States.
• Washington University in St. Louis, Saint Louis, Missouri, United States.
• National Cancer Institute, Gaithersburg, MD, United States.
• Broad Institute, Cambridge, MA, United States.
• National Cancer Institute, ROCKVILLE, MD, United States.
• National Cancer Institute, Rockville, Maryland, United States.
• Washington University in St. Louis, St. Louis, MO, United States.
• Washington University in St. Louis, St Louis, Missouri, United States.

Both acquired mutations and germline genetic variation are known risk factors for chronic lymphocytic leukemia (CLL). Joint characterization of germline, acquired, and clinical risk has the potential to improve CLL risk prediction. Here, we investigated whether inclusion of a CLL-associated polygenic score (PGS) and two common types of clonal hematopoiesis (CH), autosomal mosaic chromosomal alterations (mCAs) and CH of indeterminate potential (CHIP), could improve CLL risk stratification in 436,784 participants in the UK Biobank and a replication set of 35,382 participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Individual mCAs on chromosomes 11, 12, 23, 14, and 22, as well as CHIP mutations in known lymphoid driver genes, were strongly associated with CLL risk. Integrative models that included sex, age, smoking status, blood cell traits, genetic similarity, CLL PGS, autosomal mCAs, and CHIP had the greatest discriminative ability with predictive utility waning five years after measurement of CH. Sensitivity analyses removing individuals with abnormal blood cell counts and CH commonly observed in CLL showed persistent increased discriminative ability. Evaluating cumulative absolute risk, the CLL PGS and CH had improved ability to stratify CLL cases into higher risk categories and controls into lower risk categories. Overall, this analysis details the enhanced ability to identify individuals at high risk of CLL when integrating germline and somatic data derived from peripheral blood.