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Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia
Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply...
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Published in: | Carcinogenesis (New York) 2015-11, Vol.36 (11), p.1314-1326 |
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creator | Brenner, Darren R Amos, Christopher I Brhane, Yonathan Timofeeva, Maria N Caporaso, Neil Wang, Yufei Christiani, David C Bickeböller, Heike Yang, Ping Albanes, Demetrius Stevens, Victoria L Gapstur, Susan McKay, James Boffetta, Paolo Zaridze, David Szeszenia-Dabrowska, Neonilia Lissowska, Jolanta Rudnai, Peter Fabianova, Eleonora Mates, Dana Bencko, Vladimir Foretova, Lenka Janout, Vladimir Krokan, Hans E Skorpen, Frank Gabrielsen, Maiken E Vatten, Lars Njølstad, Inger Chen, Chu Goodman, Gary Lathrop, Mark Vooder, Tõnu Välk, Kristjan Nelis, Mari Metspalu, Andres Broderick, Peter Eisen, Timothy Wu, Xifeng Zhang, Di Chen, Wei Spitz, Margaret R Wei, Yongyue Su, Li Xie, Dong She, Jun Matsuo, Keitaro Matsuda, Fumihiko Ito, Hidemi Risch, Angela Heinrich, Joachim Rosenberger, Albert Muley, Thomas Dienemann, Hendrik Field, John K Raji, Olaide Chen, Ying Gosney, John Liloglou, Triantafillos Davies, Michael P A Marcus, Michael McLaughlin, John Orlow, Irene Han, Younghun Li, Yafang Zong, Xuchen Johansson, Mattias Liu, Geoffrey Tworoger, Shelley S Le Marchand, Loic Henderson, Brian E Wilkens, Lynne R Dai, Juncheng Shen, Hongbing Houlston, Richard S Landi, Maria T Brennan, Paul Hung, Rayjean J |
description | Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range. |
doi_str_mv | 10.1093/carcin/bgv128 |
format | article |
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Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.</description><identifier>ISSN: 0143-3334</identifier><identifier>ISSN: 1460-2180</identifier><identifier>EISSN: 1460-2180</identifier><identifier>DOI: 10.1093/carcin/bgv128</identifier><identifier>PMID: 26363033</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Adenocarcinoma - genetics ; Adenocarcinoma - pathology ; Bayes Theorem ; Carcinoma, Squamous Cell - genetics ; Carcinoma, Squamous Cell - pathology ; Case-Control Studies ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Lung Neoplasms - genetics ; Lung Neoplasms - pathology ; Original Manuscript</subject><ispartof>Carcinogenesis (New York), 2015-11, Vol.36 (11), p.1314-1326</ispartof><rights>The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</rights><rights>The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com. 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c491t-dc7c1b67e630a2d8f7cc964e7564409ef29f368917a00716ff6aee82a15a412f3</citedby><cites>FETCH-LOGICAL-c491t-dc7c1b67e630a2d8f7cc964e7564409ef29f368917a00716ff6aee82a15a412f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26363033$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-116965$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Brenner, Darren R</creatorcontrib><creatorcontrib>Amos, Christopher I</creatorcontrib><creatorcontrib>Brhane, Yonathan</creatorcontrib><creatorcontrib>Timofeeva, Maria N</creatorcontrib><creatorcontrib>Caporaso, Neil</creatorcontrib><creatorcontrib>Wang, Yufei</creatorcontrib><creatorcontrib>Christiani, David C</creatorcontrib><creatorcontrib>Bickeböller, Heike</creatorcontrib><creatorcontrib>Yang, Ping</creatorcontrib><creatorcontrib>Albanes, Demetrius</creatorcontrib><creatorcontrib>Stevens, Victoria L</creatorcontrib><creatorcontrib>Gapstur, Susan</creatorcontrib><creatorcontrib>McKay, James</creatorcontrib><creatorcontrib>Boffetta, Paolo</creatorcontrib><creatorcontrib>Zaridze, David</creatorcontrib><creatorcontrib>Szeszenia-Dabrowska, Neonilia</creatorcontrib><creatorcontrib>Lissowska, Jolanta</creatorcontrib><creatorcontrib>Rudnai, Peter</creatorcontrib><creatorcontrib>Fabianova, Eleonora</creatorcontrib><creatorcontrib>Mates, Dana</creatorcontrib><creatorcontrib>Bencko, Vladimir</creatorcontrib><creatorcontrib>Foretova, Lenka</creatorcontrib><creatorcontrib>Janout, Vladimir</creatorcontrib><creatorcontrib>Krokan, Hans E</creatorcontrib><creatorcontrib>Skorpen, Frank</creatorcontrib><creatorcontrib>Gabrielsen, Maiken E</creatorcontrib><creatorcontrib>Vatten, Lars</creatorcontrib><creatorcontrib>Njølstad, Inger</creatorcontrib><creatorcontrib>Chen, Chu</creatorcontrib><creatorcontrib>Goodman, Gary</creatorcontrib><creatorcontrib>Lathrop, Mark</creatorcontrib><creatorcontrib>Vooder, Tõnu</creatorcontrib><creatorcontrib>Välk, Kristjan</creatorcontrib><creatorcontrib>Nelis, Mari</creatorcontrib><creatorcontrib>Metspalu, Andres</creatorcontrib><creatorcontrib>Broderick, Peter</creatorcontrib><creatorcontrib>Eisen, Timothy</creatorcontrib><creatorcontrib>Wu, Xifeng</creatorcontrib><creatorcontrib>Zhang, Di</creatorcontrib><creatorcontrib>Chen, Wei</creatorcontrib><creatorcontrib>Spitz, Margaret R</creatorcontrib><creatorcontrib>Wei, Yongyue</creatorcontrib><creatorcontrib>Su, Li</creatorcontrib><creatorcontrib>Xie, Dong</creatorcontrib><creatorcontrib>She, Jun</creatorcontrib><creatorcontrib>Matsuo, Keitaro</creatorcontrib><creatorcontrib>Matsuda, Fumihiko</creatorcontrib><creatorcontrib>Ito, Hidemi</creatorcontrib><creatorcontrib>Risch, Angela</creatorcontrib><creatorcontrib>Heinrich, Joachim</creatorcontrib><creatorcontrib>Rosenberger, Albert</creatorcontrib><creatorcontrib>Muley, Thomas</creatorcontrib><creatorcontrib>Dienemann, Hendrik</creatorcontrib><creatorcontrib>Field, John K</creatorcontrib><creatorcontrib>Raji, Olaide</creatorcontrib><creatorcontrib>Chen, Ying</creatorcontrib><creatorcontrib>Gosney, John</creatorcontrib><creatorcontrib>Liloglou, Triantafillos</creatorcontrib><creatorcontrib>Davies, Michael P A</creatorcontrib><creatorcontrib>Marcus, Michael</creatorcontrib><creatorcontrib>McLaughlin, John</creatorcontrib><creatorcontrib>Orlow, Irene</creatorcontrib><creatorcontrib>Han, Younghun</creatorcontrib><creatorcontrib>Li, Yafang</creatorcontrib><creatorcontrib>Zong, Xuchen</creatorcontrib><creatorcontrib>Johansson, Mattias</creatorcontrib><creatorcontrib>Liu, Geoffrey</creatorcontrib><creatorcontrib>Tworoger, Shelley S</creatorcontrib><creatorcontrib>Le Marchand, Loic</creatorcontrib><creatorcontrib>Henderson, Brian E</creatorcontrib><creatorcontrib>Wilkens, Lynne R</creatorcontrib><creatorcontrib>Dai, Juncheng</creatorcontrib><creatorcontrib>Shen, Hongbing</creatorcontrib><creatorcontrib>Houlston, Richard S</creatorcontrib><creatorcontrib>Landi, Maria T</creatorcontrib><creatorcontrib>Brennan, Paul</creatorcontrib><creatorcontrib>Hung, Rayjean J</creatorcontrib><creatorcontrib>EPIC Investigators</creatorcontrib><creatorcontrib>EPIC Investigators</creatorcontrib><title>Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia</title><title>Carcinogenesis (New York)</title><addtitle>Carcinogenesis</addtitle><description>Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.</description><subject>Adenocarcinoma - genetics</subject><subject>Adenocarcinoma - pathology</subject><subject>Bayes Theorem</subject><subject>Carcinoma, Squamous Cell - genetics</subject><subject>Carcinoma, Squamous Cell - pathology</subject><subject>Case-Control Studies</subject><subject>Genetic Predisposition to Disease</subject><subject>Genome-Wide Association Study</subject><subject>Humans</subject><subject>Lung Neoplasms - genetics</subject><subject>Lung Neoplasms - pathology</subject><subject>Original Manuscript</subject><issn>0143-3334</issn><issn>1460-2180</issn><issn>1460-2180</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNpVkdtu1DAQhi0EokvhklvkFwi1Y68T3yCVcFpppUqocGvNOnZiyNqR7d3V8iw8LK5CC70aaeb75_Qj9JqSt5RIdqUhauevdsOR1u0TtKJckKqmLXmKVoRyVjHG-AV6kdIPQqhga_kcXdSCCUYYW6Hfm9747KzTkF3wOFg8HfyANXhtIh5dymEKw7lKs9F3GD5CdOBzwjDP09kV9j2cTSo5bCPszSnEn_cQnqML0WX3a-leJDGAHk3CJ5dH53EeDb79uum2GHyPN9uuu8E6-BRidvASPbMwJfPqb7xE3z59vO2-VNubz5vueltpLmmuet1ouhONKTdB3be20VoKbpq14JxIY2tpmWglbYCQhgprBRjT1kDXwGlt2SWqlr7pZObDTpWt9xDPKoBTH9z3axXioA77g6JUSLEu_LuFL_De9Lp8MML0SPa44t2ohnBUvPxfCPlvoI4hpWjsg5YSdWerWmxVi62Ff_P_wAf63kf2BwW9pjI</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Brenner, Darren R</creator><creator>Amos, Christopher I</creator><creator>Brhane, Yonathan</creator><creator>Timofeeva, Maria N</creator><creator>Caporaso, Neil</creator><creator>Wang, 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Xuchen</creator><creator>Johansson, Mattias</creator><creator>Liu, Geoffrey</creator><creator>Tworoger, Shelley S</creator><creator>Le Marchand, Loic</creator><creator>Henderson, Brian E</creator><creator>Wilkens, Lynne R</creator><creator>Dai, Juncheng</creator><creator>Shen, Hongbing</creator><creator>Houlston, Richard S</creator><creator>Landi, Maria T</creator><creator>Brennan, Paul</creator><creator>Hung, Rayjean J</creator><general>Oxford University Press</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>5PM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D93</scope></search><sort><creationdate>20151101</creationdate><title>Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia</title><author>Brenner, Darren R ; Amos, Christopher I ; Brhane, Yonathan ; Timofeeva, Maria N ; Caporaso, Neil ; Wang, Yufei ; Christiani, David C ; Bickeböller, Heike ; Yang, Ping ; Albanes, Demetrius ; Stevens, Victoria L ; Gapstur, Susan ; McKay, James ; Boffetta, Paolo ; Zaridze, David ; Szeszenia-Dabrowska, Neonilia ; Lissowska, Jolanta ; Rudnai, Peter ; Fabianova, Eleonora ; Mates, Dana ; Bencko, Vladimir ; Foretova, Lenka ; Janout, Vladimir ; Krokan, Hans E ; Skorpen, Frank ; Gabrielsen, Maiken E ; Vatten, Lars ; Njølstad, Inger ; Chen, Chu ; Goodman, Gary ; Lathrop, Mark ; Vooder, Tõnu ; Välk, Kristjan ; Nelis, Mari ; Metspalu, Andres ; Broderick, Peter ; Eisen, Timothy ; Wu, Xifeng ; Zhang, Di ; Chen, Wei ; Spitz, Margaret R ; Wei, Yongyue ; Su, Li ; Xie, Dong ; She, Jun ; Matsuo, Keitaro ; Matsuda, Fumihiko ; Ito, Hidemi ; Risch, Angela ; Heinrich, Joachim ; Rosenberger, Albert ; Muley, Thomas ; Dienemann, Hendrik ; Field, John K ; Raji, Olaide ; Chen, Ying ; Gosney, John ; Liloglou, Triantafillos ; Davies, Michael P A ; Marcus, Michael ; McLaughlin, John ; Orlow, Irene ; Han, Younghun ; Li, Yafang ; Zong, Xuchen ; Johansson, Mattias ; Liu, Geoffrey ; Tworoger, Shelley S ; Le Marchand, Loic ; Henderson, Brian E ; Wilkens, Lynne R ; Dai, Juncheng ; Shen, Hongbing ; Houlston, Richard S ; Landi, Maria T ; Brennan, Paul ; Hung, Rayjean J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c491t-dc7c1b67e630a2d8f7cc964e7564409ef29f368917a00716ff6aee82a15a412f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adenocarcinoma - genetics</topic><topic>Adenocarcinoma - pathology</topic><topic>Bayes Theorem</topic><topic>Carcinoma, Squamous Cell - genetics</topic><topic>Carcinoma, Squamous Cell - pathology</topic><topic>Case-Control Studies</topic><topic>Genetic Predisposition to Disease</topic><topic>Genome-Wide Association Study</topic><topic>Humans</topic><topic>Lung Neoplasms - genetics</topic><topic>Lung Neoplasms - pathology</topic><topic>Original Manuscript</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brenner, Darren R</creatorcontrib><creatorcontrib>Amos, Christopher I</creatorcontrib><creatorcontrib>Brhane, Yonathan</creatorcontrib><creatorcontrib>Timofeeva, Maria N</creatorcontrib><creatorcontrib>Caporaso, Neil</creatorcontrib><creatorcontrib>Wang, Yufei</creatorcontrib><creatorcontrib>Christiani, David C</creatorcontrib><creatorcontrib>Bickeböller, Heike</creatorcontrib><creatorcontrib>Yang, Ping</creatorcontrib><creatorcontrib>Albanes, Demetrius</creatorcontrib><creatorcontrib>Stevens, Victoria L</creatorcontrib><creatorcontrib>Gapstur, Susan</creatorcontrib><creatorcontrib>McKay, James</creatorcontrib><creatorcontrib>Boffetta, Paolo</creatorcontrib><creatorcontrib>Zaridze, David</creatorcontrib><creatorcontrib>Szeszenia-Dabrowska, Neonilia</creatorcontrib><creatorcontrib>Lissowska, Jolanta</creatorcontrib><creatorcontrib>Rudnai, Peter</creatorcontrib><creatorcontrib>Fabianova, Eleonora</creatorcontrib><creatorcontrib>Mates, Dana</creatorcontrib><creatorcontrib>Bencko, Vladimir</creatorcontrib><creatorcontrib>Foretova, Lenka</creatorcontrib><creatorcontrib>Janout, Vladimir</creatorcontrib><creatorcontrib>Krokan, Hans E</creatorcontrib><creatorcontrib>Skorpen, Frank</creatorcontrib><creatorcontrib>Gabrielsen, Maiken E</creatorcontrib><creatorcontrib>Vatten, Lars</creatorcontrib><creatorcontrib>Njølstad, Inger</creatorcontrib><creatorcontrib>Chen, Chu</creatorcontrib><creatorcontrib>Goodman, Gary</creatorcontrib><creatorcontrib>Lathrop, Mark</creatorcontrib><creatorcontrib>Vooder, Tõnu</creatorcontrib><creatorcontrib>Välk, Kristjan</creatorcontrib><creatorcontrib>Nelis, Mari</creatorcontrib><creatorcontrib>Metspalu, Andres</creatorcontrib><creatorcontrib>Broderick, Peter</creatorcontrib><creatorcontrib>Eisen, Timothy</creatorcontrib><creatorcontrib>Wu, Xifeng</creatorcontrib><creatorcontrib>Zhang, Di</creatorcontrib><creatorcontrib>Chen, Wei</creatorcontrib><creatorcontrib>Spitz, Margaret R</creatorcontrib><creatorcontrib>Wei, Yongyue</creatorcontrib><creatorcontrib>Su, Li</creatorcontrib><creatorcontrib>Xie, Dong</creatorcontrib><creatorcontrib>She, Jun</creatorcontrib><creatorcontrib>Matsuo, Keitaro</creatorcontrib><creatorcontrib>Matsuda, Fumihiko</creatorcontrib><creatorcontrib>Ito, Hidemi</creatorcontrib><creatorcontrib>Risch, Angela</creatorcontrib><creatorcontrib>Heinrich, Joachim</creatorcontrib><creatorcontrib>Rosenberger, Albert</creatorcontrib><creatorcontrib>Muley, Thomas</creatorcontrib><creatorcontrib>Dienemann, Hendrik</creatorcontrib><creatorcontrib>Field, John K</creatorcontrib><creatorcontrib>Raji, Olaide</creatorcontrib><creatorcontrib>Chen, Ying</creatorcontrib><creatorcontrib>Gosney, John</creatorcontrib><creatorcontrib>Liloglou, Triantafillos</creatorcontrib><creatorcontrib>Davies, Michael P A</creatorcontrib><creatorcontrib>Marcus, Michael</creatorcontrib><creatorcontrib>McLaughlin, John</creatorcontrib><creatorcontrib>Orlow, Irene</creatorcontrib><creatorcontrib>Han, Younghun</creatorcontrib><creatorcontrib>Li, Yafang</creatorcontrib><creatorcontrib>Zong, Xuchen</creatorcontrib><creatorcontrib>Johansson, Mattias</creatorcontrib><creatorcontrib>Liu, Geoffrey</creatorcontrib><creatorcontrib>Tworoger, Shelley S</creatorcontrib><creatorcontrib>Le Marchand, Loic</creatorcontrib><creatorcontrib>Henderson, Brian E</creatorcontrib><creatorcontrib>Wilkens, Lynne R</creatorcontrib><creatorcontrib>Dai, Juncheng</creatorcontrib><creatorcontrib>Shen, Hongbing</creatorcontrib><creatorcontrib>Houlston, Richard S</creatorcontrib><creatorcontrib>Landi, Maria T</creatorcontrib><creatorcontrib>Brennan, Paul</creatorcontrib><creatorcontrib>Hung, Rayjean J</creatorcontrib><creatorcontrib>EPIC Investigators</creatorcontrib><creatorcontrib>EPIC Investigators</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Umeå universitet</collection><jtitle>Carcinogenesis (New York)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Brenner, Darren R</au><au>Amos, Christopher I</au><au>Brhane, Yonathan</au><au>Timofeeva, Maria N</au><au>Caporaso, Neil</au><au>Wang, Yufei</au><au>Christiani, David C</au><au>Bickeböller, Heike</au><au>Yang, Ping</au><au>Albanes, Demetrius</au><au>Stevens, Victoria L</au><au>Gapstur, Susan</au><au>McKay, James</au><au>Boffetta, Paolo</au><au>Zaridze, David</au><au>Szeszenia-Dabrowska, Neonilia</au><au>Lissowska, Jolanta</au><au>Rudnai, Peter</au><au>Fabianova, Eleonora</au><au>Mates, Dana</au><au>Bencko, Vladimir</au><au>Foretova, Lenka</au><au>Janout, Vladimir</au><au>Krokan, Hans E</au><au>Skorpen, Frank</au><au>Gabrielsen, Maiken E</au><au>Vatten, Lars</au><au>Njølstad, Inger</au><au>Chen, Chu</au><au>Goodman, Gary</au><au>Lathrop, Mark</au><au>Vooder, Tõnu</au><au>Välk, Kristjan</au><au>Nelis, Mari</au><au>Metspalu, Andres</au><au>Broderick, Peter</au><au>Eisen, Timothy</au><au>Wu, Xifeng</au><au>Zhang, Di</au><au>Chen, Wei</au><au>Spitz, Margaret R</au><au>Wei, Yongyue</au><au>Su, Li</au><au>Xie, Dong</au><au>She, Jun</au><au>Matsuo, Keitaro</au><au>Matsuda, Fumihiko</au><au>Ito, Hidemi</au><au>Risch, Angela</au><au>Heinrich, Joachim</au><au>Rosenberger, Albert</au><au>Muley, Thomas</au><au>Dienemann, Hendrik</au><au>Field, John K</au><au>Raji, Olaide</au><au>Chen, Ying</au><au>Gosney, John</au><au>Liloglou, Triantafillos</au><au>Davies, Michael P A</au><au>Marcus, Michael</au><au>McLaughlin, John</au><au>Orlow, Irene</au><au>Han, Younghun</au><au>Li, Yafang</au><au>Zong, Xuchen</au><au>Johansson, Mattias</au><au>Liu, Geoffrey</au><au>Tworoger, Shelley S</au><au>Le Marchand, Loic</au><au>Henderson, Brian E</au><au>Wilkens, Lynne R</au><au>Dai, Juncheng</au><au>Shen, Hongbing</au><au>Houlston, Richard S</au><au>Landi, Maria T</au><au>Brennan, Paul</au><au>Hung, Rayjean J</au><aucorp>EPIC Investigators</aucorp><aucorp>EPIC Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia</atitle><jtitle>Carcinogenesis (New York)</jtitle><addtitle>Carcinogenesis</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>36</volume><issue>11</issue><spage>1314</spage><epage>1326</epage><pages>1314-1326</pages><issn>0143-3334</issn><issn>1460-2180</issn><eissn>1460-2180</eissn><abstract>Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>26363033</pmid><doi>10.1093/carcin/bgv128</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0143-3334 |
ispartof | Carcinogenesis (New York), 2015-11, Vol.36 (11), p.1314-1326 |
issn | 0143-3334 1460-2180 1460-2180 |
language | eng |
recordid | cdi_swepub_primary_oai_DiVA_org_umu_116965 |
source | Oxford Journals Online |
subjects | Adenocarcinoma - genetics Adenocarcinoma - pathology Bayes Theorem Carcinoma, Squamous Cell - genetics Carcinoma, Squamous Cell - pathology Case-Control Studies Genetic Predisposition to Disease Genome-Wide Association Study Humans Lung Neoplasms - genetics Lung Neoplasms - pathology Original Manuscript |
title | Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia |
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