Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method

Mattias Johansson; Angus Roberts; Dan Chen; Yaoyong Li; Manon Delahaye-Sourdeix; Niraj Aswani; Mark A. Greenwood; Simone Benhamou; Pagona Lagiou; Ivana Holcátová; Lorenzo Richiardi; Kristina Kjaerheim; Antonio Agudo; Xavier Castellsagué; Tatiana V. Macfarlane; Luigi Barzan; Cristina Canova; Nalin S. Thakker; David I. Conway; Ariana Znaor; Claire M. Healy; Wolfgang Ahrens; David Zaridze; Neonilia Szeszenia-Dabrowska; Jolanta Lissowska; Eleonóra Fabiánová; Ioan Nicolae Mates; Vladimir Bencko; Lenka Foretova; Vladimir Janout; Maria Paula Curado; Sergio Koifman; Ana Menezes; Victor Wünsch-Filho; Jose Eluf-Neto; Paolo Boffetta; Silvia Franceschi; Rolando Herrero; Leticia Fernandez Garrote; Renato Talamini; Stefania Boccia; Pilar Galan; Lars Vatten; Peter Thomson; Diana Zelenika; Mark Lathrop; Graham Byrnes; Hamish Cunningham; Paul Brennan; Jon Wakefield; James D. Mckay

doi:10.1371/journal.pone.0036888

Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method

Mattias Johansson
, Angus Roberts
, Dan Chen
, Yaoyong Li
, Manon Delahaye-Sourdeix
, Niraj Aswani
, Mark A. Greenwood
, Simone Benhamou
, Pagona Lagiou
, Ivana Holcátová
, Lorenzo Richiardi
, Kristina Kjaerheim
, Antonio Agudo
, Xavier Castellsagué
, Tatiana V. Macfarlane
, Luigi Barzan
, Cristina Canova
, Nalin S. Thakker
, David I. Conway
, Ariana Znaor

Claire M. Healy, Wolfgang Ahrens, David Zaridze, Neonilia Szeszenia-Dabrowska, Jolanta Lissowska, Eleonóra Fabiánová, Ioan Nicolae Mates, Vladimir Bencko, Lenka Foretova, Vladimir Janout, Maria Paula Curado, Sergio Koifman, Ana Menezes, Victor Wünsch-Filho, Jose Eluf-Neto, Paolo Boffetta, Silvia Franceschi, Rolando Herrero, Leticia Fernandez Garrote, Renato Talamini, Stefania Boccia, Pilar Galan, Lars Vatten, Peter Thomson, Diana Zelenika, Mark Lathrop, Graham Byrnes, Hamish Cunningham, Paul Brennan, Jon Wakefield, James D. Mckay

International Agency for Research on Cancer
University of Sheffield
University of Manchester
Institut national de la santé et de la recherche médicale
University of Paris Sud
National and Kapodistrian University of Athens
Charles University
University of Turin
Cancer Registry of Norway Institute of Population-Based Cancer Research
Bellvitge Biomedical Research Institute
CIBER Epidemiología y Salud Pública (CIBERESP)
University of Aberdeen
General Hospital of Pordenone
University of Padua
Imperial College London
University of Glasgow
Croatian National Institute of Public Health
Trinity College Dublin
Leibniz Institute for Prevention Research and Epidemiology
University of Bremen
Blokhin Cancer Research Center
Nofer Institute of Occupational Medicine
Maria Sklodowska-Curie Institute of Oncology
Regional Authority of Public Health
Carol Davila University of Medicine and Pharmacy
Masaryk Memorial Cancer Institute
Palacký University Olomouc
University of Strathclyde
Hospital Araujo Jorge da ACCG
Fundação Oswaldo Cruz
Universidade Federal de Pelotas
Universidade de São Paulo
Instituto de Investigación Epidemiológica
National School of Public Health
IRCCS Centro di Riferimento Oncologico - Aviano PN
Catholic University of the Sacred Heart
IRCCS San Raffaele Pisana - Roma
CRNH IdF
Norwegian University of Science and Technology
Newcastle University
Institut Génomique, Commissariat À l'Énergie Atomique
Fondation Jean Dausset - CEPH
University of Washington

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p_trend] = 2.5×10^-3). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

Original language	English
Article number	e36888
Journal	PLoS ONE
Volume	7
Issue number	5
DOIs	https://doi.org/10.1371/journal.pone.0036888
State	Published - May 25 2012

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Johansson, M., Roberts, A., Chen, D., Li, Y., Delahaye-Sourdeix, M., Aswani, N., Greenwood, M. A., Benhamou, S., Lagiou, P., Holcátová, I., Richiardi, L., Kjaerheim, K., Agudo, A., Castellsagué, X., Macfarlane, T. V., Barzan, L., Canova, C., Thakker, N. S., Conway, D. I., ... Mckay, J. D. (2012). Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method. PLoS ONE, 7(5), Article e36888. https://doi.org/10.1371/journal.pone.0036888

@article{6b15ddd178724062b40e81cbfc3716d3,

title = "Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method",

abstract = "Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [ptrend] = 2.5×10-3). The combined OR for having one additional rare allele was 0.83 (95\% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).",

author = "Mattias Johansson and Angus Roberts and Dan Chen and Yaoyong Li and Manon Delahaye-Sourdeix and Niraj Aswani and Greenwood, \{Mark A.\} and Simone Benhamou and Pagona Lagiou and Ivana Holc{\'a}tov{\'a} and Lorenzo Richiardi and Kristina Kjaerheim and Antonio Agudo and Xavier Castellsagu{\'e} and Macfarlane, \{Tatiana V.\} and Luigi Barzan and Cristina Canova and Thakker, \{Nalin S.\} and Conway, \{David I.\} and Ariana Znaor and Healy, \{Claire M.\} and Wolfgang Ahrens and David Zaridze and Neonilia Szeszenia-Dabrowska and Jolanta Lissowska and Eleon{\'o}ra Fabi{\'a}nov{\'a} and Mates, \{Ioan Nicolae\} and Vladimir Bencko and Lenka Foretova and Vladimir Janout and Curado, \{Maria Paula\} and Sergio Koifman and Ana Menezes and Victor W{\"u}nsch-Filho and Jose Eluf-Neto and Paolo Boffetta and Silvia Franceschi and Rolando Herrero and Garrote, \{Leticia Fernandez\} and Renato Talamini and Stefania Boccia and Pilar Galan and Lars Vatten and Peter Thomson and Diana Zelenika and Mark Lathrop and Graham Byrnes and Hamish Cunningham and Paul Brennan and Jon Wakefield and Mckay, \{James D.\}",

year = "2012",

month = may,

day = "25",

doi = "10.1371/journal.pone.0036888",

language = "English",

volume = "7",

journal = "PLoS ONE",

issn = "1932-6203",

number = "5",

}

Johansson, M, Roberts, A, Chen, D, Li, Y, Delahaye-Sourdeix, M, Aswani, N, Greenwood, MA, Benhamou, S, Lagiou, P, Holcátová, I, Richiardi, L, Kjaerheim, K, Agudo, A, Castellsagué, X, Macfarlane, TV, Barzan, L, Canova, C, Thakker, NS, Conway, DI, Znaor, A, Healy, CM, Ahrens, W, Zaridze, D, Szeszenia-Dabrowska, N, Lissowska, J, Fabiánová, E, Mates, IN, Bencko, V, Foretova, L, Janout, V, Curado, MP, Koifman, S, Menezes, A, Wünsch-Filho, V, Eluf-Neto, J, Boffetta, P, Franceschi, S, Herrero, R, Garrote, LF, Talamini, R, Boccia, S, Galan, P, Vatten, L, Thomson, P, Zelenika, D, Lathrop, M, Byrnes, G, Cunningham, H, Brennan, P, Wakefield, J & Mckay, JD 2012, 'Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method', PLoS ONE, vol. 7, no. 5, e36888. https://doi.org/10.1371/journal.pone.0036888

TY - JOUR

T1 - Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method

AU - Johansson, Mattias

AU - Roberts, Angus

AU - Chen, Dan

AU - Li, Yaoyong

AU - Delahaye-Sourdeix, Manon

AU - Aswani, Niraj

AU - Greenwood, Mark A.

AU - Benhamou, Simone

AU - Lagiou, Pagona

AU - Holcátová, Ivana

AU - Richiardi, Lorenzo

AU - Kjaerheim, Kristina

AU - Agudo, Antonio

AU - Castellsagué, Xavier

AU - Macfarlane, Tatiana V.

AU - Barzan, Luigi

AU - Canova, Cristina

AU - Thakker, Nalin S.

AU - Conway, David I.

AU - Znaor, Ariana

AU - Healy, Claire M.

AU - Ahrens, Wolfgang

AU - Zaridze, David

AU - Szeszenia-Dabrowska, Neonilia

AU - Lissowska, Jolanta

AU - Fabiánová, Eleonóra

AU - Mates, Ioan Nicolae

AU - Bencko, Vladimir

AU - Foretova, Lenka

AU - Janout, Vladimir

AU - Curado, Maria Paula

AU - Koifman, Sergio

AU - Menezes, Ana

AU - Wünsch-Filho, Victor

AU - Eluf-Neto, Jose

AU - Boffetta, Paolo

AU - Franceschi, Silvia

AU - Herrero, Rolando

AU - Garrote, Leticia Fernandez

AU - Talamini, Renato

AU - Boccia, Stefania

AU - Galan, Pilar

AU - Vatten, Lars

AU - Thomson, Peter

AU - Zelenika, Diana

AU - Lathrop, Mark

AU - Byrnes, Graham

AU - Cunningham, Hamish

AU - Brennan, Paul

AU - Wakefield, Jon

AU - Mckay, James D.

PY - 2012/5/25

Y1 - 2012/5/25

N2 - Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [ptrend] = 2.5×10-3). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

AB - Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [ptrend] = 2.5×10-3). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

UR - https://www.scopus.com/pages/publications/84861470791

U2 - 10.1371/journal.pone.0036888

DO - 10.1371/journal.pone.0036888

M3 - Article

C2 - 22662130

AN - SCOPUS:84861470791

SN - 1932-6203

VL - 7

JO - PLoS ONE

JF - PLoS ONE

IS - 5

M1 - e36888

ER -

Using prior information from the medical literature in GWAS of oral cancer identifies novel susceptibility variant on Chromosome 4 - the AdAPT method

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