Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

• Published in: PloS one Vol. 7; no. 6; p. e39236
• Main Authors: Ribeiro, Ricardo J T, Monteiro, Cátia P D, Azevedo, Andreia S M, Cunha, Virgínia F M, Ramanakumar, Agnihotram V, Fraga, Avelino M, Pina, Francisco M, Lopes, Carlos M S, Medeiros, Rui M, Franco, Eduardo L
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.06.2012; Public Library of Science (PLoS)
• Subjects: Adipokines - genetics; Adipokines - metabolism; Age; Aged; Angiogenesis; Biomarkers; Biopsy; Biopsy - methods; Cancer; Cancer metastasis; Case-Control Studies; Chromosomes; Development and progression; Disease prevention; Epidemiology; Genetic aspects; Genetic diversity; Genetic Predisposition to Disease; Genetic variance; Health aspects; Health risk assessment; Health risks; Humans; Logistic Models; Male; Medical diagnosis; Medicine; Metastases; Metastasis; Oncology; Pathogenesis; Pathways; Polymorphism, Single Nucleotide; Predictions; Predictive Value of Tests; Prostate cancer; Prostatic Neoplasms - genetics; Prostatic Neoplasms - metabolism; Quality; Reclassification; Risk; Risk factors; ROC Curve; Signal Transduction; Single nucleotide polymorphisms; Single-nucleotide polymorphism; Studies; Urology; Canada; Montreal Quebec Canada; Portugal
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0039236

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.