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Article: Population-standardized genetic risk score: The SNP-based method of choice for inherited risk assessment of prostate cancer

TitlePopulation-standardized genetic risk score: The SNP-based method of choice for inherited risk assessment of prostate cancer
Authors
Keywordsgenetic risk score
prostate cancer
single nucleotide polymorphisms
Issue Date2016
Citation
Asian Journal of Andrology, 2016, v. 18, n. 4, p. 520-524 How to Cite?
AbstractSeveral different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.
Persistent Identifierhttp://hdl.handle.net/10722/314350
ISSN
2021 Impact Factor: 3.054
2020 SCImago Journal Rankings: 0.701
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorConran, Carly-
dc.contributor.authorNa, Rong-
dc.contributor.authorChen, Haitao-
dc.contributor.authorJiang, Deke-
dc.contributor.authorLin, Xiaoling-
dc.contributor.authorZheng, S.-
dc.contributor.authorBrendler, Charles-
dc.contributor.authorXu, Jianfeng-
dc.date.accessioned2022-07-20T12:03:43Z-
dc.date.available2022-07-20T12:03:43Z-
dc.date.issued2016-
dc.identifier.citationAsian Journal of Andrology, 2016, v. 18, n. 4, p. 520-524-
dc.identifier.issn1008-682X-
dc.identifier.urihttp://hdl.handle.net/10722/314350-
dc.description.abstractSeveral different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.-
dc.languageeng-
dc.relation.ispartofAsian Journal of Andrology-
dc.subjectgenetic risk score-
dc.subjectprostate cancer-
dc.subjectsingle nucleotide polymorphisms-
dc.titlePopulation-standardized genetic risk score: The SNP-based method of choice for inherited risk assessment of prostate cancer-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.4103/1008-682X.179527-
dc.identifier.pmid27080480-
dc.identifier.pmcidPMC4955173-
dc.identifier.scopuseid_2-s2.0-84977619049-
dc.identifier.volume18-
dc.identifier.issue4-
dc.identifier.spage520-
dc.identifier.epage524-
dc.identifier.eissn1745-7262-
dc.identifier.isiWOS:000380245900005-

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