Linda Kachuri, PhD @Linda_Kachuri @WitteLab @UCSF_Epibiostat @UCSFCancer #AACR22 Genetic Determinants Of PSA Levels

Linda Kachuri, PhD @Linda_Kachuri @WitteLab @UCSF_Epibiostat @UCSFCancer #AACR22 Genetic Determinants Of PSA Levels
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Linda Kachuri, PhD, Postdoctoral Scholar, Epidemiology & Biostatistics at UC San Francisco. In this video, she speaks about the AACR 2022 Abstract - 1441 / 8 - Genetic determinants of PSA levels improve prostate cancer screening.




PSA screening for prostate cancer (PCa) remains contentious due to low sensitivity and specificity, which leads to overdiagnosis and overtreatment. Our study's goal is to identify genetic drivers of PSA levels in cancer-free men in order to tailor PCa screening. We expect that accounting for PSA variance that is related to genetic factors and does not reflect PCa will enhance test accuracy.

We used data from the UK Biobank, BioVU, PLCO, and Kaiser Permanente cohorts to undertake the largest genome-wide association study (GWAS) of PSA in men without PCa (N=95,768; 85,924 primarily European ancestry). Our GWAS identified 129 PSA-related SNPs (P510-8), 82 of which were new. Two cancer prevention trials, PCPT (n=5737) and SELECT (n=22,247), successfully validated a polygenic score (PGSPSA) composed of these 129 variations. In PCPT, PGSPSA explained 7.3 percent (p=7.010-98) of the variation in baseline PSA and 8.7 percent (p=7.010-476) in SELECT. Importantly, in PCPT (OR=0.98, p=0.71) or SELECT (OR=1.04, p=0.98), PGSPSA was not linked with PCa status, confirming that it reflects benign PSA variation.


The potential clinical value of PSA genetic correction was investigated by assessing reclassification at biopsy referral thresholds in a real-world context at Kaiser Permanente. We projected that adopting PGSPSA correction would have prevented 21.2 percent of negative biopsies in non-cases. Reclassification below the biopsy referral threshold was also more likely in instances, especially in those with low-grade illness with a Gleason score of 7. (7.3 percent below vs. 2.6 percent above). Overall, genetic PSA correction tended to increase referral decision accuracy, with a Net Reclassification Index of 0.148.


Following that, we looked at genetically adjusted PSA in the context of detecting aggressive PCa, which was defined as a Gleason score of 7, PSA of 10 ng/mL, T3-T4 stage, and/or distant or nodal metastases. When genetically adjusted baseline PSA was added to a baseline model with age and trial arm, it was more significantly related with aggressive PCa and provided a greater area under the curve (AUC) in PCPT (OR=3.03, p=3.510-7; AUC: 0.72 vs. 0.68) and SELECT (OR=3.37, p=3.510-11; AUC: 0.78 vs. 0.74). Furthermore, genetically adjusted PSA adds to the information provided by PCa risk variations. In PCPT, a logistic regression model that included genetically corrected PSA and the 269-variant PGSPCa achieved a significantly higher AUC for aggressive PCa (AUC: 0.73 vs. 0.65, p=3.310-4) and overall PCa (AUC=0.69 vs. 0.66, p=3.310-6).


Our findings show that taking genetic determinants of PSA into consideration has the potential to reduce wasteful testing and overdiagnosis of low-risk PCa while increasing identification of aggressive disease. To fully describe the genetic basis of PSA variation and enhance its therapeutic value, larger and more diverse study populations are required.