Genetic variations in immune mediators and prostate cancer risk: A field synopsis with Bayesian calculations

•The rs1143627 and rs1946518 polymorphisms were noteworthy by Bayesian calculations.•There was a high degree of co-expression among IL1B, IL6, IL8 and PTGS2 genes.•The protein–protein network showed that IL-1B was co-expressed with IL-8. Our study aimed to revaluate the significant data from meta-an...

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Veröffentlicht in:Cytokine (Philadelphia, Pa.) Pa.), 2024-07, Vol.179, p.156630, Article 156630
Hauptverfasser: Santos Freire, Matheus, Victor de Oliveira Monteiro, André, Moura Martins, Tayane, Socorro Silva Lima Duarte, Márcia, Carlos Lima, Antonio, Luiz Araújo Bentes Leal, Alessandro, Rodolfo Pereira da Silva, Felipe, Fernando Marques Barcellos, José
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container_title Cytokine (Philadelphia, Pa.)
container_volume 179
creator Santos Freire, Matheus
Victor de Oliveira Monteiro, André
Moura Martins, Tayane
Socorro Silva Lima Duarte, Márcia
Carlos Lima, Antonio
Luiz Araújo Bentes Leal, Alessandro
Rodolfo Pereira da Silva, Felipe
Fernando Marques Barcellos, José
description •The rs1143627 and rs1946518 polymorphisms were noteworthy by Bayesian calculations.•There was a high degree of co-expression among IL1B, IL6, IL8 and PTGS2 genes.•The protein–protein network showed that IL-1B was co-expressed with IL-8. Our study aimed to revaluate the significant data from meta-analyses on genetic variations in immune mediators and the risk of prostate cancer (PCa) by Bayesian approaches. We performed a search on the literature before September 5th, 2023, for meta-analytic studies on polymorphisms in immune mediator genes and the risk of PCa. Two Bayesian approaches were used to assess the level of noteworthiness in the meta-analytic data: the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10−3 and 10−6. The quality evaluation of studies was performed with the Venice criteria. Gene-gene and protein–protein networks were designed for the genes and products enrolled in the results. As results, 18 meta-analyses on 17 polymorphisms in several immune mediator genes were included (IL1B rs16944/rs1143627, IL4 rs2243250/rs2227284/rs2070874, IL6 1800795/rs1800796/rs1800797, IL8 rs4073, IL10 rs1800896/rs1800871/rs1800872, IL18 rs1946518, COX2 rs2745557, TNFA rs361525 and PTGS2 rs20417/689470). The Bayesian calculations showed the rs1143627 and the rs1946518 polymorphisms in IL1B and IL18 genes, respectively, were noteworthy. The Venice criteria showed that only four studies received the highest level of evidence. The gene-gene and protein–protein networks reinforced the findings on IL1B and IL18 genes. In conclusion, this current Bayesian revaluation showed that the rs1143627 and the rs1946518 polymorphisms in the IL1B and IL18 genes, respectively, were noteworthy biomarker candidates for PCa risk.
doi_str_mv 10.1016/j.cyto.2024.156630
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Our study aimed to revaluate the significant data from meta-analyses on genetic variations in immune mediators and the risk of prostate cancer (PCa) by Bayesian approaches. We performed a search on the literature before September 5th, 2023, for meta-analytic studies on polymorphisms in immune mediator genes and the risk of PCa. Two Bayesian approaches were used to assess the level of noteworthiness in the meta-analytic data: the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10−3 and 10−6. The quality evaluation of studies was performed with the Venice criteria. Gene-gene and protein–protein networks were designed for the genes and products enrolled in the results. As results, 18 meta-analyses on 17 polymorphisms in several immune mediator genes were included (IL1B rs16944/rs1143627, IL4 rs2243250/rs2227284/rs2070874, IL6 1800795/rs1800796/rs1800797, IL8 rs4073, IL10 rs1800896/rs1800871/rs1800872, IL18 rs1946518, COX2 rs2745557, TNFA rs361525 and PTGS2 rs20417/689470). The Bayesian calculations showed the rs1143627 and the rs1946518 polymorphisms in IL1B and IL18 genes, respectively, were noteworthy. The Venice criteria showed that only four studies received the highest level of evidence. The gene-gene and protein–protein networks reinforced the findings on IL1B and IL18 genes. 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Our study aimed to revaluate the significant data from meta-analyses on genetic variations in immune mediators and the risk of prostate cancer (PCa) by Bayesian approaches. We performed a search on the literature before September 5th, 2023, for meta-analytic studies on polymorphisms in immune mediator genes and the risk of PCa. Two Bayesian approaches were used to assess the level of noteworthiness in the meta-analytic data: the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10−3 and 10−6. The quality evaluation of studies was performed with the Venice criteria. Gene-gene and protein–protein networks were designed for the genes and products enrolled in the results. As results, 18 meta-analyses on 17 polymorphisms in several immune mediator genes were included (IL1B rs16944/rs1143627, IL4 rs2243250/rs2227284/rs2070874, IL6 1800795/rs1800796/rs1800797, IL8 rs4073, IL10 rs1800896/rs1800871/rs1800872, IL18 rs1946518, COX2 rs2745557, TNFA rs361525 and PTGS2 rs20417/689470). The Bayesian calculations showed the rs1143627 and the rs1946518 polymorphisms in IL1B and IL18 genes, respectively, were noteworthy. The Venice criteria showed that only four studies received the highest level of evidence. The gene-gene and protein–protein networks reinforced the findings on IL1B and IL18 genes. In conclusion, this current Bayesian revaluation showed that the rs1143627 and the rs1946518 polymorphisms in the IL1B and IL18 genes, respectively, were noteworthy biomarker candidates for PCa risk.</description><subject>Bayes Theorem</subject><subject>Bayesian approach</subject><subject>Cytokine</subject><subject>Genetic polymorphisms</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Variation</subject><subject>Humans</subject><subject>Interleukin-1beta - genetics</subject><subject>Interleukins</subject><subject>Male</subject><subject>Meta-analysis</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>Prostatic neoplasms</subject><subject>Prostatic Neoplasms - genetics</subject><subject>Risk Factors</subject><issn>1043-4666</issn><issn>1096-0023</issn><issn>1096-0023</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kMFO3DAQQK2qqFDoD3BAPnLJdmInTlL1QhGlSEi9lLPljCeql8RZbIdq_75eQjn2ZMt68-R5jJ2XsCmhVJ-3G9yneSNAVJuyVkrCO3ZSQqcKACHfH-6VLCql1DH7GOMWADrZNB_YsWxVp9pWnLDxljwlh_zZBGeSm33kznM3TYsnPpHNj3OI3HjLd2GOySTiaDxS4MHFxy_8ig-ORsvj3s-76CL_49Jv_s3sKTrjMzviMq7mM3Y0mDHSp9fzlD18v_l1_aO4_3l7d311X6CEJhV9M5DFCmowSkCD2PalrcXQilYY6FGhsgPWVd2B6rGzPZJB01VV_YIrecouV2_-8dNCMenJRaRxNJ7mJWqZ1Z3sKmgyKlYU83Ix0KB3wU0m7HUJ-lBZb_Whsj5U1mvlPHTx6l_6nOht5F_WDHxdAcpbPjsKOqKjHM26QJi0nd3__H8BcS6QPQ</recordid><startdate>202407</startdate><enddate>202407</enddate><creator>Santos Freire, Matheus</creator><creator>Victor de Oliveira Monteiro, André</creator><creator>Moura Martins, Tayane</creator><creator>Socorro Silva Lima Duarte, Márcia</creator><creator>Carlos Lima, Antonio</creator><creator>Luiz Araújo Bentes Leal, Alessandro</creator><creator>Rodolfo Pereira da Silva, Felipe</creator><creator>Fernando Marques Barcellos, José</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202407</creationdate><title>Genetic variations in immune mediators and prostate cancer risk: A field synopsis with Bayesian calculations</title><author>Santos Freire, Matheus ; Victor de Oliveira Monteiro, André ; Moura Martins, Tayane ; Socorro Silva Lima Duarte, Márcia ; Carlos Lima, Antonio ; Luiz Araújo Bentes Leal, Alessandro ; Rodolfo Pereira da Silva, Felipe ; Fernando Marques Barcellos, José</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c307t-b7fedc4050a6207cc8b1d52f8282a0bc6c6dfc545906bc9dbceaca94456207c63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Bayes Theorem</topic><topic>Bayesian approach</topic><topic>Cytokine</topic><topic>Genetic polymorphisms</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Variation</topic><topic>Humans</topic><topic>Interleukin-1beta - genetics</topic><topic>Interleukins</topic><topic>Male</topic><topic>Meta-analysis</topic><topic>Polymorphism, Single Nucleotide - genetics</topic><topic>Prostatic neoplasms</topic><topic>Prostatic Neoplasms - genetics</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Santos Freire, Matheus</creatorcontrib><creatorcontrib>Victor de Oliveira Monteiro, André</creatorcontrib><creatorcontrib>Moura Martins, Tayane</creatorcontrib><creatorcontrib>Socorro Silva Lima Duarte, Márcia</creatorcontrib><creatorcontrib>Carlos Lima, Antonio</creatorcontrib><creatorcontrib>Luiz Araújo Bentes Leal, Alessandro</creatorcontrib><creatorcontrib>Rodolfo Pereira da Silva, Felipe</creatorcontrib><creatorcontrib>Fernando Marques Barcellos, José</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Cytokine (Philadelphia, Pa.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Santos Freire, Matheus</au><au>Victor de Oliveira Monteiro, André</au><au>Moura Martins, Tayane</au><au>Socorro Silva Lima Duarte, Márcia</au><au>Carlos Lima, Antonio</au><au>Luiz Araújo Bentes Leal, Alessandro</au><au>Rodolfo Pereira da Silva, Felipe</au><au>Fernando Marques Barcellos, José</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic variations in immune mediators and prostate cancer risk: A field synopsis with Bayesian calculations</atitle><jtitle>Cytokine (Philadelphia, Pa.)</jtitle><addtitle>Cytokine</addtitle><date>2024-07</date><risdate>2024</risdate><volume>179</volume><spage>156630</spage><pages>156630-</pages><artnum>156630</artnum><issn>1043-4666</issn><issn>1096-0023</issn><eissn>1096-0023</eissn><abstract>•The rs1143627 and rs1946518 polymorphisms were noteworthy by Bayesian calculations.•There was a high degree of co-expression among IL1B, IL6, IL8 and PTGS2 genes.•The protein–protein network showed that IL-1B was co-expressed with IL-8. Our study aimed to revaluate the significant data from meta-analyses on genetic variations in immune mediators and the risk of prostate cancer (PCa) by Bayesian approaches. We performed a search on the literature before September 5th, 2023, for meta-analytic studies on polymorphisms in immune mediator genes and the risk of PCa. Two Bayesian approaches were used to assess the level of noteworthiness in the meta-analytic data: the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10−3 and 10−6. The quality evaluation of studies was performed with the Venice criteria. Gene-gene and protein–protein networks were designed for the genes and products enrolled in the results. As results, 18 meta-analyses on 17 polymorphisms in several immune mediator genes were included (IL1B rs16944/rs1143627, IL4 rs2243250/rs2227284/rs2070874, IL6 1800795/rs1800796/rs1800797, IL8 rs4073, IL10 rs1800896/rs1800871/rs1800872, IL18 rs1946518, COX2 rs2745557, TNFA rs361525 and PTGS2 rs20417/689470). The Bayesian calculations showed the rs1143627 and the rs1946518 polymorphisms in IL1B and IL18 genes, respectively, were noteworthy. The Venice criteria showed that only four studies received the highest level of evidence. The gene-gene and protein–protein networks reinforced the findings on IL1B and IL18 genes. In conclusion, this current Bayesian revaluation showed that the rs1143627 and the rs1946518 polymorphisms in the IL1B and IL18 genes, respectively, were noteworthy biomarker candidates for PCa risk.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>38696882</pmid><doi>10.1016/j.cyto.2024.156630</doi></addata></record>
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subjects Bayes Theorem
Bayesian approach
Cytokine
Genetic polymorphisms
Genetic Predisposition to Disease
Genetic Variation
Humans
Interleukin-1beta - genetics
Interleukins
Male
Meta-analysis
Polymorphism, Single Nucleotide - genetics
Prostatic neoplasms
Prostatic Neoplasms - genetics
Risk Factors
title Genetic variations in immune mediators and prostate cancer risk: A field synopsis with Bayesian calculations
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