Utility of polygenic risk scores (PRS) in predicting pancreatic cancer: a systematic review and meta-analysis of common variant and mixed scores with insights into rare variant analysis
Utility of polygenic risk scores (PRS) in predicting pancreatic cancer: a systematic review and meta-analysis of common variant and mixed scores with insights into rare variant analysis
Introduction: pancreatic cancer remains among the top five causes of cancer-related mortality. Only 18% to 20% of patients present with early-stage, potentially curable disease. Patient risk stratification is critical to increasing the number of individuals eligible for surgery. Polygenic risk scores (PRS), combined with clinical risk factors, offer a promising approach to assess lifetime risk of pancreatic cancer. This systematic review synthesizes the results of all published PRS and mixed models for pancreatic cancer.
Methods: we systematically searched MEDLINE, Embase, Ovid and Web of Science databases. Odds ratios reported between risk quintiles were transformed to OR per SD increase in risk score. Reported AUCs were synthesized and compared between PRS and mixed models.
Results: 27 studies were identified for formal synthesis. PRS yielded an OR of 1.40 (1.28-1.53) for pancreatic cancer, while mixed models incorporating clinical risk factors showed a higher OR of 1.58 (1.34 - 1.88). The AUCs for PRS was 0.61 (0.58-0.65), compared to 0.70 (0.61-0.80) for mixed models. The predictive power of PRS models was positively correlated with the number of SNPs included in studies. Ancestry significantly influenced prediction accuracy, with an OR of 1.42 (1.30-1.56) in Caucasian populations compared to 1.21 (0.77-1.90) in Asian populations.
Conclusions: adding clinical risk factors to PRS models significantly increases their predictive capability. Further research is needed to identify a comprehensive set of risk SNPs, enhance accuracy across diverse populations, and incorporate rare genetic variants. These advancements have the potential to significantly boost the predictive accuracy of PRS and mixed models.
pancreatic cancer; polygenic risk scores; genetic scores; clinical risk scores; risk stratification; pancreatic adenocarcinoma; risk prediction, pancreatic adenocarcinoma, pancreatic cancer, risk stratification, risk prediction, clinical risk scores, genetic scores, polygenic risk scores
Verras, Georgios Ioannis
6e71c2d9-b915-419a-b073-5626c33f5bd1
Hamady, Zaed Z.
545a1c81-276e-4341-a420-aa10aa5d8ca8
Collins, Andrew
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Tapper, William
9d5ddc92-a8dd-4c78-ac67-c5867b62724c
13 January 2025
Verras, Georgios Ioannis
6e71c2d9-b915-419a-b073-5626c33f5bd1
Hamady, Zaed Z.
545a1c81-276e-4341-a420-aa10aa5d8ca8
Collins, Andrew
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Tapper, William
9d5ddc92-a8dd-4c78-ac67-c5867b62724c
Verras, Georgios Ioannis, Hamady, Zaed Z., Collins, Andrew and Tapper, William
(2025)
Utility of polygenic risk scores (PRS) in predicting pancreatic cancer: a systematic review and meta-analysis of common variant and mixed scores with insights into rare variant analysis.
Cancers, 17 (2), [241].
(doi:10.3390/cancers17020241).
Abstract
Introduction: pancreatic cancer remains among the top five causes of cancer-related mortality. Only 18% to 20% of patients present with early-stage, potentially curable disease. Patient risk stratification is critical to increasing the number of individuals eligible for surgery. Polygenic risk scores (PRS), combined with clinical risk factors, offer a promising approach to assess lifetime risk of pancreatic cancer. This systematic review synthesizes the results of all published PRS and mixed models for pancreatic cancer.
Methods: we systematically searched MEDLINE, Embase, Ovid and Web of Science databases. Odds ratios reported between risk quintiles were transformed to OR per SD increase in risk score. Reported AUCs were synthesized and compared between PRS and mixed models.
Results: 27 studies were identified for formal synthesis. PRS yielded an OR of 1.40 (1.28-1.53) for pancreatic cancer, while mixed models incorporating clinical risk factors showed a higher OR of 1.58 (1.34 - 1.88). The AUCs for PRS was 0.61 (0.58-0.65), compared to 0.70 (0.61-0.80) for mixed models. The predictive power of PRS models was positively correlated with the number of SNPs included in studies. Ancestry significantly influenced prediction accuracy, with an OR of 1.42 (1.30-1.56) in Caucasian populations compared to 1.21 (0.77-1.90) in Asian populations.
Conclusions: adding clinical risk factors to PRS models significantly increases their predictive capability. Further research is needed to identify a comprehensive set of risk SNPs, enhance accuracy across diverse populations, and incorporate rare genetic variants. These advancements have the potential to significantly boost the predictive accuracy of PRS and mixed models.
Text
Utility of Polygenic Risk Scores (PRSs) in Predicting Pancreatic Cancer: A Systematic Review and Meta-Analysis of Common-Variant and Mixed Scores with Insights into Rare Variant Analysis
- Accepted Manuscript
Text
cancers-17-00241
- Version of Record
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Accepted/In Press date: 8 January 2025
e-pub ahead of print date: 13 January 2025
Published date: 13 January 2025
Keywords:
pancreatic cancer; polygenic risk scores; genetic scores; clinical risk scores; risk stratification; pancreatic adenocarcinoma; risk prediction, pancreatic adenocarcinoma, pancreatic cancer, risk stratification, risk prediction, clinical risk scores, genetic scores, polygenic risk scores
Identifiers
Local EPrints ID: 498182
URI: http://eprints.soton.ac.uk/id/eprint/498182
ISSN: 2072-6694
PURE UUID: 785877f2-77d9-4fe5-b105-3fdc6a1e6769
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Date deposited: 12 Feb 2025 17:32
Last modified: 22 Aug 2025 02:45
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Author:
Georgios Ioannis Verras
Author:
Zaed Z. Hamady
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