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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
Main Authors: 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
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cited_by cdi_FETCH-LOGICAL-c491t-dc7c1b67e630a2d8f7cc964e7564409ef29f368917a00716ff6aee82a15a412f3
cites cdi_FETCH-LOGICAL-c491t-dc7c1b67e630a2d8f7cc964e7564409ef29f368917a00716ff6aee82a15a412f3
container_end_page 1326
container_issue 11
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container_title Carcinogenesis (New York)
container_volume 36
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
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Additional variants within the suggestive range (0.0001&gt; P &gt; 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. 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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 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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&gt; P &gt; 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. 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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 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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&gt; P &gt; 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>
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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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