Rebecca Graff

Early Career Tenure-track Researcher, University of California, San Francisco

1 active project

PSA Genetics

Prostate-specific antigen (PSA) testing reduces prostate cancer (PCa) mortality. However, PSA screening has declined in recent years due to concerns about overdiagnosis and overtreatment of PCa. If PSA testing could be personalized, then its burdens would not be as great…

Scientific Questions Being Studied

Prostate-specific antigen (PSA) testing reduces prostate cancer (PCa) mortality. However, PSA screening has declined in recent years due to concerns about overdiagnosis and overtreatment of PCa. If PSA testing could be personalized, then its burdens would not be as great and it could prove even more effective in preventing PCa deaths. Given the high heritability of PSA, personalization based on genetics has the potential to be extremely effective. Genetic factors that impact PSA levels but not PCa risk reduce the ability of PSA to predict PCa; by properly accounting for them we can increase the relative variation in PSA that reflects PCa and improve the clinical utility of PSA testing. Therefore, we propose to undertake a large-scale, multi-ancestry PSA genetics study. We will comprehensively discover and characterize genetic factors associated with PSA levels independently of PCa and develop and apply prediction models for PCa outcomes that incorporate genetic factors.

Project Purpose(s)

  • Disease Focused Research (prostate-specific antigen levels, prostate cancer)
  • Ancestry

Scientific Approaches

In addition to All of Us, we will include data on men from upwards of 50 collaborating studies, selected because they have information on PSA testing, genome-wide genetics, and PCa status confirmed by medical records or cancer registries. To discover genetic factors underlying PSA levels, we will undertake GWAS, TWAS, and multi-ancestry fine mapping. We will then characterize genetic contributors to PSA levels by implementing conditional and mediation analyses that identify overlap between GWAS and TWAS signals and, separately, between PSA and PCa signals. Finally, we will develop precision PSA-based prediction models of PCa outcomes, both with and without genetics, that indicate whether a man should undergo prostate biopsy.

Anticipated Findings

We hypothesize that: 1) a large-scale multi-ancestry search will uncover genetic factors accounting for a substantial portion of PSA variation; 2) considerable genetic factors will be associated with PSA independent of PCa, and combining them in risk scores will result in strong predictors of constitutive PSA levels; and 3) accounting for genetic factors affecting PSA and known PCa risk variants will predict PCa outcomes better than PSA alone and will improve clinical decision making for men undergoing PCa screening. The long-term result will be a reduction in unnecessary procedures and their associated morbidities, as well as decreased overdiagnosis and overtreatment of PCa.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Research Team

Owner:

  • Rebecca Graff - Early Career Tenure-track Researcher, University of California, San Francisco
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