| Title: | Polygenic Risk Score Predicts Prostate Cancer Risk Independent of Type 2 Diabetes |
| Journal: | Diabetes Obesity and Metabolism |
| Published: | 26 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41883289/ |
| DOI: | https://doi.org/10.1111/dom.70690 |
Publication 18185
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Abstract
AIMS: Type 2 diabetes mellitus (T2DM) has been inversely associated with prostate cancer (PrCa) risk. However, it remains unclear whether a polygenic risk score (PRS) for PrCa can effectively stratify risk among men with T2DM. The primary objective of this study was to assess whether a PrCa PRS predicts PrCa risk independently of T2DM status. The secondary objective was to evaluate potential mediating factors, including insulin-like growth factor-1 (IGF-1) and sex hormones.</p>
MATERIALS AND METHODS: We analysed data from over 140 000 men in the UK Biobank and Penn Medicine Biobank. A PrCa PRS was constructed using summary statistics from a large-scale genome-wide association study. Cox proportional hazards models were used to evaluate the association between PRS and incident PrCa, adjusting for relevant covariates and testing for interaction by T2DM status. Additionally, sex hormones and IGF-1 levels were analysed to explore potential mediators.</p>
RESULTS: T2DM was associated with a reduced incidence of PrCa. The PrCa PRS was significantly associated with PrCa risk regardless of T2DM status (p < 0.001), and men in the highest PRS category exhibited the greatest risk, especially among those without T2DM. IGF-1 levels were positively associated with PrCa risk among both diabetic and non-diabetic men, while sex hormone levels showed no significant association in men with T2DM. Adjusting for testosterone and IGF-1 did not attenuate the association between PRS and PrCa.</p>
CONCLUSIONS: PrCa PRS effectively stratifies risk among men with and without T2DM, highlighting the independent contribution of genetic susceptibility. Lower IGF-1 levels in T2DM patients may partly mediate the reduced PrCa risk, suggesting a possible biological mechanism underlying these observations.</p>
7 Authors
- Guk Jin Lee
- Sang-Hyuk Jung
- Jonghyun Lee
- Ki Won Moon
- Penn Medicine Biobank
- Jae-Seung Yun
- Dokyoon Kim
1 Application
| Application ID | Title |
|---|---|
| 90981 | Development of a comprehensive predictive model for glaucoma occurence |
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