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Genome-wide two-locus epistasis scans in prostate cancer using two European populations

Identifieur interne : 003689 ( Pmc/Corpus ); précédent : 003688; suivant : 003690

Genome-wide two-locus epistasis scans in prostate cancer using two European populations

Auteurs : Sha Tao ; Junjie Feng ; Timothy Webster ; Guangfu Jin ; Fang-Chi Hsu ; Shyh-Huei Chen ; Seong-Tae Kim ; Zhong Wang ; Zheng Zhang ; Siqun L. Zheng ; William B. Isaacs ; Jianfeng Xu ; Jielin Sun

Source :

RBID : PMC:3634576

Abstract

Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene–gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene–gene interaction and PCa risk, we performed a two-stage genome-wide gene–gene interaction scan using a novel statistical approach named “Boolean Operation-based Screening and Testing”. In the first stage, we exhaustively evaluated all pairs of SNP–SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP–SNP interaction reached a genome-wide significant level of 4.4E–13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP–SNP interactions (Pinteraction < 1.0E–08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP–SNP interactions were significant in the JHH population at a Pinteraction cutoff of 0.01. However, none of the 16 pairs of SNP–SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP–SNP interactions that can be followed in other replication studies.


Url:
DOI: 10.1007/s00439-012-1148-4
PubMed: 22367438
PubMed Central: 3634576

Links to Exploration step

PMC:3634576

Le document en format XML

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<p id="P2">Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene–gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene–gene interaction and PCa risk, we performed a two-stage genome-wide gene–gene interaction scan using a novel statistical approach named “Boolean Operation-based Screening and Testing”. In the first stage, we exhaustively evaluated all pairs of SNP–SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP–SNP interaction reached a genome-wide significant level of 4.4E–13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP–SNP interactions (
<italic>P</italic>
<sub>interaction</sub>
< 1.0E–08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP–SNP interactions were significant in the JHH population at a
<italic>P</italic>
<sub>interaction</sub>
cutoff of 0.01. However, none of the 16 pairs of SNP–SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP–SNP interactions that can be followed in other replication studies.</p>
</div>
</front>
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<article-title>Genome-wide two-locus epistasis scans in prostate cancer using two European populations</article-title>
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<name>
<surname>Tao</surname>
<given-names>Sha</given-names>
</name>
<aff id="A1">Center for Genetic Epidemiology and Prevention, Van Andel Research Institute, Grand Rapids, MI, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Feng</surname>
<given-names>Junjie</given-names>
</name>
<aff id="A2">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A3">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
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<name>
<surname>Webster</surname>
<given-names>Timothy</given-names>
</name>
<aff id="A4">Center for Genetic Epidemiology and Prevention, Van Andel Research Institute, Grand Rapids, MI, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jin</surname>
<given-names>Guangfu</given-names>
</name>
<aff id="A5">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A6">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
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<name>
<surname>Hsu</surname>
<given-names>Fang-Chi</given-names>
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<aff id="A7">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A8">Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Shyh-Huei</given-names>
</name>
<aff id="A9">Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kim</surname>
<given-names>Seong-Tae</given-names>
</name>
<aff id="A10">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A11">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Zhong</given-names>
</name>
<aff id="A12">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A13">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Zheng</given-names>
</name>
<aff id="A14">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A15">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zheng</surname>
<given-names>Siqun L.</given-names>
</name>
<aff id="A16">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A17">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Isaacs</surname>
<given-names>William B.</given-names>
</name>
<aff id="A18">Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA</aff>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Jianfeng</given-names>
</name>
<aff id="A19">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A20">Center for Genetic Epidemiology and Prevention, Van Andel Research Institute, Grand Rapids, MI, USA</aff>
<aff id="A21">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
<aff id="A22">Department of Urology, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Sun</surname>
<given-names>Jielin</given-names>
</name>
<email>jisun@wakehealth.edu</email>
<aff id="A23">Center for Cancer Genomics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157, USA</aff>
<aff id="A24">Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA</aff>
</contrib>
</contrib-group>
<author-notes>
<fn id="FN1" fn-type="equal">
<p id="P1">S. Tao and J. Feng contributed equally.</p>
</fn>
</author-notes>
<pub-date pub-type="nihms-submitted">
<day>11</day>
<month>3</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="epub">
<day>26</day>
<month>2</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="ppub">
<month>7</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>24</day>
<month>4</month>
<year>2013</year>
</pub-date>
<volume>131</volume>
<issue>7</issue>
<fpage>1225</fpage>
<lpage>1234</lpage>
<permissions>
<copyright-statement>© Springer-Verlag 2012</copyright-statement>
<copyright-year>2012</copyright-year>
</permissions>
<abstract>
<p id="P2">Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene–gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene–gene interaction and PCa risk, we performed a two-stage genome-wide gene–gene interaction scan using a novel statistical approach named “Boolean Operation-based Screening and Testing”. In the first stage, we exhaustively evaluated all pairs of SNP–SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP–SNP interaction reached a genome-wide significant level of 4.4E–13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP–SNP interactions (
<italic>P</italic>
<sub>interaction</sub>
< 1.0E–08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP–SNP interactions were significant in the JHH population at a
<italic>P</italic>
<sub>interaction</sub>
cutoff of 0.01. However, none of the 16 pairs of SNP–SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP–SNP interactions that can be followed in other replication studies.</p>
</abstract>
<funding-group>
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<funding-source country="United States">National Cancer Institute : NCI</funding-source>
<award-id>P50 CA058236 || CA</award-id>
</award-group>
</funding-group>
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</front>
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