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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">GWAS of Follicular Lymphoma Reveals Allelic Heterogeneity at 6p21.32
and Suggests Shared Genetic Susceptibility with Diffuse Large B-cell
Lymphoma</title><author><name sortKey="Smedby, Karin E" sort="Smedby, Karin E" uniqKey="Smedby K" first="Karin E." last="Smedby">Karin E. Smedby</name><affiliation><nlm:aff id="aff1"><addr-line>Department of Medicine, Clinical Epidemiology Unit, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Foo, Jia Nee" sort="Foo, Jia Nee" uniqKey="Foo J" first="Jia Nee" last="Foo">Jia Nee Foo</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Skibola, Christine F" sort="Skibola, Christine F" uniqKey="Skibola C" first="Christine F." last="Skibola">Christine F. Skibola</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Darabi, Hatef" sort="Darabi, Hatef" uniqKey="Darabi H" first="Hatef" last="Darabi">Hatef Darabi</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Conde, Lucia" sort="Conde, Lucia" uniqKey="Conde L" first="Lucia" last="Conde">Lucia Conde</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hjalgrim, Henrik" sort="Hjalgrim, Henrik" uniqKey="Hjalgrim H" first="Henrik" last="Hjalgrim">Henrik Hjalgrim</name><affiliation><nlm:aff id="aff5"><addr-line>Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kumar, Vikrant" sort="Kumar, Vikrant" uniqKey="Kumar V" first="Vikrant" last="Kumar">Vikrant Kumar</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Chang, Ellen T" sort="Chang, Ellen T" uniqKey="Chang E" first="Ellen T." last="Chang">Ellen T. Chang</name><affiliation><nlm:aff id="aff6"><addr-line>Cancer Prevention Institute of California, Fremont, California, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff7"><addr-line>Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Rothman, Nathaniel" sort="Rothman, Nathaniel" uniqKey="Rothman N" first="Nathaniel" last="Rothman">Nathaniel Rothman</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Cerhan, James R" sort="Cerhan, James R" uniqKey="Cerhan J" first="James R." last="Cerhan">James R. Cerhan</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brooks Wilson, Angela R" sort="Brooks Wilson, Angela R" uniqKey="Brooks Wilson A" first="Angela R." last="Brooks-Wilson">Angela R. Brooks-Wilson</name><affiliation><nlm:aff id="aff10"><addr-line>British Columbia Cancer Research Center, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff11"><addr-line>Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Rehnberg, Emil" sort="Rehnberg, Emil" uniqKey="Rehnberg E" first="Emil" last="Rehnberg">Emil Rehnberg</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Irwan, Ishak D" sort="Irwan, Ishak D" uniqKey="Irwan I" first="Ishak D." last="Irwan">Ishak D. Irwan</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ryder, Lars P" sort="Ryder, Lars P" uniqKey="Ryder L" first="Lars P." last="Ryder">Lars P. Ryder</name><affiliation><nlm:aff id="aff12"><addr-line>Department of Clinical Immunology, University Hospital of Copenhagen, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brown, Peter N" sort="Brown, Peter N" uniqKey="Brown P" first="Peter N." last="Brown">Peter N. Brown</name><affiliation><nlm:aff id="aff13"><addr-line>Department of Haematology, Copenhagen University Hospital, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bracci, Paige M" sort="Bracci, Paige M" uniqKey="Bracci P" first="Paige M." last="Bracci">Paige M. Bracci</name><affiliation><nlm:aff id="aff14"><addr-line>Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Agana, Luz" sort="Agana, Luz" uniqKey="Agana L" first="Luz" last="Agana">Luz Agana</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Riby, Jacques" sort="Riby, Jacques" uniqKey="Riby J" first="Jacques" last="Riby">Jacques Riby</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Cozen, Wendy" sort="Cozen, Wendy" uniqKey="Cozen W" first="Wendy" last="Cozen">Wendy Cozen</name><affiliation><nlm:aff id="aff15"><addr-line>Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Davis, Scott" sort="Davis, Scott" uniqKey="Davis S" first="Scott" last="Davis">Scott Davis</name><affiliation><nlm:aff id="aff16"><addr-line>Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff17"><addr-line>University of Washington, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hartge, Patricia" sort="Hartge, Patricia" uniqKey="Hartge P" first="Patricia" last="Hartge">Patricia Hartge</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Morton, Lindsay M" sort="Morton, Lindsay M" uniqKey="Morton L" first="Lindsay M." last="Morton">Lindsay M. Morton</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Severson, Richard K" sort="Severson, Richard K" uniqKey="Severson R" first="Richard K." last="Severson">Richard K. Severson</name><affiliation><nlm:aff id="aff18"><addr-line>Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, Michigan, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff19"><addr-line>Karmanos Cancer Institute, Detroit, Michigan, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Wang, Sophia S" sort="Wang, Sophia S" uniqKey="Wang S" first="Sophia S." last="Wang">Sophia S. Wang</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff20"><addr-line>Division of Etiology, Beckman Research Institute and the City of Hope, Duarte, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Slager, Susan L" sort="Slager, Susan L" uniqKey="Slager S" first="Susan L." last="Slager">Susan L. Slager</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Fredericksen, Zachary S" sort="Fredericksen, Zachary S" uniqKey="Fredericksen Z" first="Zachary S." last="Fredericksen">Zachary S. Fredericksen</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Novak, Anne J" sort="Novak, Anne J" uniqKey="Novak A" first="Anne J." last="Novak">Anne J. Novak</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kay, Neil E" sort="Kay, Neil E" uniqKey="Kay N" first="Neil E." last="Kay">Neil E. Kay</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Habermann, Thomas M" sort="Habermann, Thomas M" uniqKey="Habermann T" first="Thomas M." last="Habermann">Thomas M. Habermann</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Armstrong, Bruce" sort="Armstrong, Bruce" uniqKey="Armstrong B" first="Bruce" last="Armstrong">Bruce Armstrong</name><affiliation><nlm:aff id="aff21"><addr-line>Sydney School of Public Health, The University of Sydney, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kricker, Anne" sort="Kricker, Anne" uniqKey="Kricker A" first="Anne" last="Kricker">Anne Kricker</name><affiliation><nlm:aff id="aff21"><addr-line>Sydney School of Public Health, The University of Sydney, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Milliken, Sam" sort="Milliken, Sam" uniqKey="Milliken S" first="Sam" last="Milliken">Sam Milliken</name><affiliation><nlm:aff id="aff22"><addr-line>Department of Haematology, St. Vincent's Hospital, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Purdue, Mark P" sort="Purdue, Mark P" uniqKey="Purdue M" first="Mark P." last="Purdue">Mark P. Purdue</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Vajdic, Claire M" sort="Vajdic, Claire M" uniqKey="Vajdic C" first="Claire M." last="Vajdic">Claire M. Vajdic</name><affiliation><nlm:aff id="aff23"><addr-line>University of New South Wales Cancer Research Center, Prince of Wales Clinical School, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Boyle, Peter" sort="Boyle, Peter" uniqKey="Boyle P" first="Peter" last="Boyle">Peter Boyle</name><affiliation><nlm:aff id="aff24"><addr-line>International Prevention Research Institute, Lyon, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Lan, Qing" sort="Lan, Qing" uniqKey="Lan Q" first="Qing" last="Lan">Qing Lan</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zahm, Shelia H" sort="Zahm, Shelia H" uniqKey="Zahm S" first="Shelia H." last="Zahm">Shelia H. Zahm</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zhang, Yawei" sort="Zhang, Yawei" uniqKey="Zhang Y" first="Yawei" last="Zhang">Yawei Zhang</name><affiliation><nlm:aff id="aff25"><addr-line>School of Public Health, Yale University, New Haven, Connecticut, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zheng, Tongzhang" sort="Zheng, Tongzhang" uniqKey="Zheng T" first="Tongzhang" last="Zheng">Tongzhang Zheng</name><affiliation><nlm:aff id="aff25"><addr-line>School of Public Health, Yale University, New Haven, Connecticut, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Leach, Stephen" sort="Leach, Stephen" uniqKey="Leach S" first="Stephen" last="Leach">Stephen Leach</name><affiliation><nlm:aff id="aff26"><addr-line>Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Spinelli, John J" sort="Spinelli, John J" uniqKey="Spinelli J" first="John J." last="Spinelli">John J. Spinelli</name><affiliation><nlm:aff id="aff10"><addr-line>British Columbia Cancer Research Center, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff27"><addr-line>School of Population and Public Health, University of British Columbia, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Smith, Martyn T" sort="Smith, Martyn T" uniqKey="Smith M" first="Martyn T." last="Smith">Martyn T. Smith</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Chanock, Stephen J" sort="Chanock, Stephen J" uniqKey="Chanock S" first="Stephen J." last="Chanock">Stephen J. Chanock</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Padyukov, Leonid" sort="Padyukov, Leonid" uniqKey="Padyukov L" first="Leonid" last="Padyukov">Leonid Padyukov</name><affiliation><nlm:aff id="aff28"><addr-line>Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Alfredsson, Lars" sort="Alfredsson, Lars" uniqKey="Alfredsson L" first="Lars" last="Alfredsson">Lars Alfredsson</name><affiliation><nlm:aff id="aff29"><addr-line>Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Klareskog, Lars" sort="Klareskog, Lars" uniqKey="Klareskog L" first="Lars" last="Klareskog">Lars Klareskog</name><affiliation><nlm:aff id="aff28"><addr-line>Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Glimelius, Bengt" sort="Glimelius, Bengt" uniqKey="Glimelius B" first="Bengt" last="Glimelius">Bengt Glimelius</name><affiliation><nlm:aff id="aff30"><addr-line>Department of Pathology and Oncology, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff31"><addr-line>Department of Radiology, Oncology, and Radiation Sciences, Uppsala University, Uppsala, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Melbye, Mads" sort="Melbye, Mads" uniqKey="Melbye M" first="Mads" last="Melbye">Mads Melbye</name><affiliation><nlm:aff id="aff5"><addr-line>Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Edison T" sort="Liu, Edison T" uniqKey="Liu E" first="Edison T." last="Liu">Edison T. Liu</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Adami, Hans Olov" sort="Adami, Hans Olov" uniqKey="Adami H" first="Hans-Olov" last="Adami">Hans-Olov Adami</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff32"><addr-line>Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Humphreys, Keith" sort="Humphreys, Keith" uniqKey="Humphreys K" first="Keith" last="Humphreys">Keith Humphreys</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Jianjun" sort="Liu, Jianjun" uniqKey="Liu J" first="Jianjun" last="Liu">Jianjun Liu</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21533074</idno><idno type="pmc">3080853</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3080853</idno><idno type="RBID">PMC:3080853</idno><idno type="doi">10.1371/journal.pgen.1001378</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">002875</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002875</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">GWAS of Follicular Lymphoma Reveals Allelic Heterogeneity at 6p21.32
and Suggests Shared Genetic Susceptibility with Diffuse Large B-cell
Lymphoma</title><author><name sortKey="Smedby, Karin E" sort="Smedby, Karin E" uniqKey="Smedby K" first="Karin E." last="Smedby">Karin E. Smedby</name><affiliation><nlm:aff id="aff1"><addr-line>Department of Medicine, Clinical Epidemiology Unit, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Foo, Jia Nee" sort="Foo, Jia Nee" uniqKey="Foo J" first="Jia Nee" last="Foo">Jia Nee Foo</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Skibola, Christine F" sort="Skibola, Christine F" uniqKey="Skibola C" first="Christine F." last="Skibola">Christine F. Skibola</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Darabi, Hatef" sort="Darabi, Hatef" uniqKey="Darabi H" first="Hatef" last="Darabi">Hatef Darabi</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Conde, Lucia" sort="Conde, Lucia" uniqKey="Conde L" first="Lucia" last="Conde">Lucia Conde</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hjalgrim, Henrik" sort="Hjalgrim, Henrik" uniqKey="Hjalgrim H" first="Henrik" last="Hjalgrim">Henrik Hjalgrim</name><affiliation><nlm:aff id="aff5"><addr-line>Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kumar, Vikrant" sort="Kumar, Vikrant" uniqKey="Kumar V" first="Vikrant" last="Kumar">Vikrant Kumar</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Chang, Ellen T" sort="Chang, Ellen T" uniqKey="Chang E" first="Ellen T." last="Chang">Ellen T. Chang</name><affiliation><nlm:aff id="aff6"><addr-line>Cancer Prevention Institute of California, Fremont, California, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff7"><addr-line>Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Rothman, Nathaniel" sort="Rothman, Nathaniel" uniqKey="Rothman N" first="Nathaniel" last="Rothman">Nathaniel Rothman</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Cerhan, James R" sort="Cerhan, James R" uniqKey="Cerhan J" first="James R." last="Cerhan">James R. Cerhan</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brooks Wilson, Angela R" sort="Brooks Wilson, Angela R" uniqKey="Brooks Wilson A" first="Angela R." last="Brooks-Wilson">Angela R. Brooks-Wilson</name><affiliation><nlm:aff id="aff10"><addr-line>British Columbia Cancer Research Center, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff11"><addr-line>Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Rehnberg, Emil" sort="Rehnberg, Emil" uniqKey="Rehnberg E" first="Emil" last="Rehnberg">Emil Rehnberg</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Irwan, Ishak D" sort="Irwan, Ishak D" uniqKey="Irwan I" first="Ishak D." last="Irwan">Ishak D. Irwan</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ryder, Lars P" sort="Ryder, Lars P" uniqKey="Ryder L" first="Lars P." last="Ryder">Lars P. Ryder</name><affiliation><nlm:aff id="aff12"><addr-line>Department of Clinical Immunology, University Hospital of Copenhagen, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Brown, Peter N" sort="Brown, Peter N" uniqKey="Brown P" first="Peter N." last="Brown">Peter N. Brown</name><affiliation><nlm:aff id="aff13"><addr-line>Department of Haematology, Copenhagen University Hospital, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Bracci, Paige M" sort="Bracci, Paige M" uniqKey="Bracci P" first="Paige M." last="Bracci">Paige M. Bracci</name><affiliation><nlm:aff id="aff14"><addr-line>Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Agana, Luz" sort="Agana, Luz" uniqKey="Agana L" first="Luz" last="Agana">Luz Agana</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Riby, Jacques" sort="Riby, Jacques" uniqKey="Riby J" first="Jacques" last="Riby">Jacques Riby</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Cozen, Wendy" sort="Cozen, Wendy" uniqKey="Cozen W" first="Wendy" last="Cozen">Wendy Cozen</name><affiliation><nlm:aff id="aff15"><addr-line>Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Davis, Scott" sort="Davis, Scott" uniqKey="Davis S" first="Scott" last="Davis">Scott Davis</name><affiliation><nlm:aff id="aff16"><addr-line>Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff17"><addr-line>University of Washington, Seattle, Washington, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hartge, Patricia" sort="Hartge, Patricia" uniqKey="Hartge P" first="Patricia" last="Hartge">Patricia Hartge</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Morton, Lindsay M" sort="Morton, Lindsay M" uniqKey="Morton L" first="Lindsay M." last="Morton">Lindsay M. Morton</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Severson, Richard K" sort="Severson, Richard K" uniqKey="Severson R" first="Richard K." last="Severson">Richard K. Severson</name><affiliation><nlm:aff id="aff18"><addr-line>Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, Michigan, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff19"><addr-line>Karmanos Cancer Institute, Detroit, Michigan, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Wang, Sophia S" sort="Wang, Sophia S" uniqKey="Wang S" first="Sophia S." last="Wang">Sophia S. Wang</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff20"><addr-line>Division of Etiology, Beckman Research Institute and the City of Hope, Duarte, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Slager, Susan L" sort="Slager, Susan L" uniqKey="Slager S" first="Susan L." last="Slager">Susan L. Slager</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Fredericksen, Zachary S" sort="Fredericksen, Zachary S" uniqKey="Fredericksen Z" first="Zachary S." last="Fredericksen">Zachary S. Fredericksen</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Novak, Anne J" sort="Novak, Anne J" uniqKey="Novak A" first="Anne J." last="Novak">Anne J. Novak</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kay, Neil E" sort="Kay, Neil E" uniqKey="Kay N" first="Neil E." last="Kay">Neil E. Kay</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Habermann, Thomas M" sort="Habermann, Thomas M" uniqKey="Habermann T" first="Thomas M." last="Habermann">Thomas M. Habermann</name><affiliation><nlm:aff id="aff9"><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Armstrong, Bruce" sort="Armstrong, Bruce" uniqKey="Armstrong B" first="Bruce" last="Armstrong">Bruce Armstrong</name><affiliation><nlm:aff id="aff21"><addr-line>Sydney School of Public Health, The University of Sydney, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kricker, Anne" sort="Kricker, Anne" uniqKey="Kricker A" first="Anne" last="Kricker">Anne Kricker</name><affiliation><nlm:aff id="aff21"><addr-line>Sydney School of Public Health, The University of Sydney, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Milliken, Sam" sort="Milliken, Sam" uniqKey="Milliken S" first="Sam" last="Milliken">Sam Milliken</name><affiliation><nlm:aff id="aff22"><addr-line>Department of Haematology, St. Vincent's Hospital, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Purdue, Mark P" sort="Purdue, Mark P" uniqKey="Purdue M" first="Mark P." last="Purdue">Mark P. Purdue</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Vajdic, Claire M" sort="Vajdic, Claire M" uniqKey="Vajdic C" first="Claire M." last="Vajdic">Claire M. Vajdic</name><affiliation><nlm:aff id="aff23"><addr-line>University of New South Wales Cancer Research Center, Prince of Wales Clinical School, Sydney, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Boyle, Peter" sort="Boyle, Peter" uniqKey="Boyle P" first="Peter" last="Boyle">Peter Boyle</name><affiliation><nlm:aff id="aff24"><addr-line>International Prevention Research Institute, Lyon, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Lan, Qing" sort="Lan, Qing" uniqKey="Lan Q" first="Qing" last="Lan">Qing Lan</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zahm, Shelia H" sort="Zahm, Shelia H" uniqKey="Zahm S" first="Shelia H." last="Zahm">Shelia H. Zahm</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zhang, Yawei" sort="Zhang, Yawei" uniqKey="Zhang Y" first="Yawei" last="Zhang">Yawei Zhang</name><affiliation><nlm:aff id="aff25"><addr-line>School of Public Health, Yale University, New Haven, Connecticut, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Zheng, Tongzhang" sort="Zheng, Tongzhang" uniqKey="Zheng T" first="Tongzhang" last="Zheng">Tongzhang Zheng</name><affiliation><nlm:aff id="aff25"><addr-line>School of Public Health, Yale University, New Haven, Connecticut, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Leach, Stephen" sort="Leach, Stephen" uniqKey="Leach S" first="Stephen" last="Leach">Stephen Leach</name><affiliation><nlm:aff id="aff26"><addr-line>Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Spinelli, John J" sort="Spinelli, John J" uniqKey="Spinelli J" first="John J." last="Spinelli">John J. Spinelli</name><affiliation><nlm:aff id="aff10"><addr-line>British Columbia Cancer Research Center, British Columbia Cancer Agency, Vancouver, Canada</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff27"><addr-line>School of Population and Public Health, University of British Columbia, Vancouver, Canada</addr-line></nlm:aff></affiliation></author><author><name sortKey="Smith, Martyn T" sort="Smith, Martyn T" uniqKey="Smith M" first="Martyn T." last="Smith">Martyn T. Smith</name><affiliation><nlm:aff id="aff3"><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Chanock, Stephen J" sort="Chanock, Stephen J" uniqKey="Chanock S" first="Stephen J." last="Chanock">Stephen J. Chanock</name><affiliation><nlm:aff id="aff8"><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Padyukov, Leonid" sort="Padyukov, Leonid" uniqKey="Padyukov L" first="Leonid" last="Padyukov">Leonid Padyukov</name><affiliation><nlm:aff id="aff28"><addr-line>Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Alfredsson, Lars" sort="Alfredsson, Lars" uniqKey="Alfredsson L" first="Lars" last="Alfredsson">Lars Alfredsson</name><affiliation><nlm:aff id="aff29"><addr-line>Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Klareskog, Lars" sort="Klareskog, Lars" uniqKey="Klareskog L" first="Lars" last="Klareskog">Lars Klareskog</name><affiliation><nlm:aff id="aff28"><addr-line>Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Glimelius, Bengt" sort="Glimelius, Bengt" uniqKey="Glimelius B" first="Bengt" last="Glimelius">Bengt Glimelius</name><affiliation><nlm:aff id="aff30"><addr-line>Department of Pathology and Oncology, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff31"><addr-line>Department of Radiology, Oncology, and Radiation Sciences, Uppsala University, Uppsala, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Melbye, Mads" sort="Melbye, Mads" uniqKey="Melbye M" first="Mads" last="Melbye">Mads Melbye</name><affiliation><nlm:aff id="aff5"><addr-line>Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Edison T" sort="Liu, Edison T" uniqKey="Liu E" first="Edison T." last="Liu">Edison T. Liu</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author><author><name sortKey="Adami, Hans Olov" sort="Adami, Hans Olov" uniqKey="Adami H" first="Hans-Olov" last="Adami">Hans-Olov Adami</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff32"><addr-line>Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America</addr-line></nlm:aff></affiliation></author><author><name sortKey="Humphreys, Keith" sort="Humphreys, Keith" uniqKey="Humphreys K" first="Keith" last="Humphreys">Keith Humphreys</name><affiliation><nlm:aff id="aff4"><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></nlm:aff></affiliation></author><author><name sortKey="Liu, Jianjun" sort="Liu, Jianjun" uniqKey="Liu J" first="Jianjun" last="Liu">Jianjun Liu</name><affiliation><nlm:aff id="aff2"><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS Genetics</title><idno type="ISSN">1553-7390</idno><idno type="eISSN">1553-7404</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Non-Hodgkin lymphoma (NHL) represents a diverse group of hematological
malignancies, of which follicular lymphoma (FL) is a prevalent subtype. A
previous genome-wide association study has established a marker, rs10484561 in
the human leukocyte antigen (HLA) class II region on 6p21.32 associated with
increased FL risk. Here, in a three-stage genome-wide association study,
starting with a genome-wide scan of 379 FL cases and 791 controls followed by
validation in 1,049 cases and 5,790 controls, we identified a second independent
FL–associated locus on 6p21.32, rs2647012
(OR<sub>combined</sub> = 0.64,
P<sub>combined</sub> = 2×10<sup>−21</sup>)
located 962 bp away from rs10484561 (r<sup>2</sup><0.1 in controls). After
mutual adjustment, the associations at the two SNPs remained genome-wide
significant (rs2647012:OR<sub>adjusted</sub> = 0.70,
P<sub>adjusted</sub> = 4×10<sup>−12</sup>;
rs10484561:OR<sub>adjusted</sub> = 1.64,
P<sub>adjusted</sub> = 5×10<sup>−15</sup>).
Haplotype and coalescence analyses indicated that rs2647012 arose on an
evolutionarily distinct haplotype from that of rs10484561 and tags a novel
allele with an opposite (protective) effect on FL risk. Moreover, in a follow-up
analysis of the top 6 FL–associated SNPs in 4,449 cases of other NHL
subtypes, rs10484561 was associated with risk of diffuse large B-cell lymphoma
(OR<sub>combined</sub> = 1.36,
P<sub>combined</sub> = 1.4×10<sup>−7</sup>).
Our results reveal the presence of allelic heterogeneity within the HLA class II
region influencing FL susceptibility and indicate a possible shared genetic
etiology with diffuse large B-cell lymphoma. These findings suggest that the HLA
class II region plays a complex yet important role in NHL.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Jaffe, Es" uniqKey="Jaffe E">ES Jaffe</name></author><author><name sortKey="Harris, Nl" uniqKey="Harris N">NL Harris</name></author><author><name sortKey="Stein, H" uniqKey="Stein H">H Stein</name></author><author><name sortKey="Vardiman, J" uniqKey="Vardiman J">J Vardiman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Morton, Lm" uniqKey="Morton L">LM Morton</name></author><author><name sortKey="Wang, Ss" uniqKey="Wang S">SS Wang</name></author><author><name sortKey="Cozen, W" uniqKey="Cozen W">W Cozen</name></author><author><name sortKey="Linet, Ms" uniqKey="Linet M">MS Linet</name></author><author><name sortKey="Chatterjee, N" uniqKey="Chatterjee N">N Chatterjee</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Altieri, A" uniqKey="Altieri A">A Altieri</name></author><author><name sortKey="Bermejo, Jl" uniqKey="Bermejo J">JL Bermejo</name></author><author><name sortKey="Hemminki, K" uniqKey="Hemminki K">K Hemminki</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chang, Et" uniqKey="Chang E">ET Chang</name></author><author><name sortKey="Smedby, Ke" uniqKey="Smedby K">KE Smedby</name></author><author><name sortKey="Hjalgrim, H" uniqKey="Hjalgrim H">H Hjalgrim</name></author><author><name sortKey="Glimelius, B" uniqKey="Glimelius B">B Glimelius</name></author><author><name sortKey="Adami, Ho" uniqKey="Adami H">HO Adami</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Skibola, Cf" uniqKey="Skibola C">CF Skibola</name></author><author><name sortKey="Bracci, Pm" uniqKey="Bracci P">PM Bracci</name></author><author><name sortKey="Halperin, E" uniqKey="Halperin E">E Halperin</name></author><author><name sortKey="Conde, L" uniqKey="Conde L">L 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sortKey="Weber, Jp" uniqKey="Weber J">JP Weber</name></author><author><name sortKey="Connors, Jm" uniqKey="Connors J">JM Connors</name></author><author><name sortKey="Gascoyne, Rd" uniqKey="Gascoyne R">RD Gascoyne</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Song, Ys" uniqKey="Song Y">YS Song</name></author><author><name sortKey="Hein, J" uniqKey="Hein J">J Hein</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bandelt, Hj" uniqKey="Bandelt H">HJ Bandelt</name></author><author><name sortKey="Forster, P" uniqKey="Forster P">P Forster</name></author><author><name sortKey="Rohl, A" uniqKey="Rohl A">A Rohl</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="De Bakker, Pi" uniqKey="De Bakker P">PI de Bakker</name></author><author><name sortKey="Mcvean, G" uniqKey="Mcvean G">G McVean</name></author><author><name sortKey="Sabeti, Pc" uniqKey="Sabeti P">PC Sabeti</name></author><author><name sortKey="Miretti, Mm" uniqKey="Miretti M">MM Miretti</name></author><author><name sortKey="Green, T" uniqKey="Green T">T Green</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Leslie, S" uniqKey="Leslie S">S Leslie</name></author><author><name sortKey="Donnelly, P" uniqKey="Donnelly P">P Donnelly</name></author><author><name sortKey="Mcvean, G" uniqKey="Mcvean G">G McVean</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wang, Ss" uniqKey="Wang S">SS Wang</name></author><author><name sortKey="Abdou, Am" uniqKey="Abdou A">AM Abdou</name></author><author><name sortKey="Morton, Lm" uniqKey="Morton L">LM Morton</name></author><author><name sortKey="Thomas, R" uniqKey="Thomas R">R Thomas</name></author><author><name sortKey="Cerhan, Jr" uniqKey="Cerhan J">JR Cerhan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Abdou, Am" uniqKey="Abdou A">AM Abdou</name></author><author><name sortKey="Gao, X" uniqKey="Gao X">X Gao</name></author><author><name sortKey="Cozen, W" uniqKey="Cozen W">W Cozen</name></author><author><name sortKey="Cerhan, Jr" uniqKey="Cerhan J">JR Cerhan</name></author><author><name sortKey="Rothman, N" uniqKey="Rothman N">N Rothman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bateman, Ac" uniqKey="Bateman A">AC Bateman</name></author><author><name sortKey="Howell, Wm" uniqKey="Howell W">WM Howell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dixon, Al" uniqKey="Dixon A">AL Dixon</name></author><author><name sortKey="Liang, L" uniqKey="Liang L">L Liang</name></author><author><name sortKey="Moffatt, Mf" uniqKey="Moffatt M">MF Moffatt</name></author><author><name sortKey="Chen, W" uniqKey="Chen W">W Chen</name></author><author><name sortKey="Heath, S" uniqKey="Heath S">S 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Genet</journal-id><journal-id journal-id-type="iso-abbrev">PLoS Genet</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosgen</journal-id><journal-title-group><journal-title>PLoS Genetics</journal-title></journal-title-group><issn pub-type="ppub">1553-7390</issn><issn pub-type="epub">1553-7404</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">21533074</article-id><article-id pub-id-type="pmc">3080853</article-id><article-id pub-id-type="publisher-id">10-PLGE-RA-NV-4214R2</article-id><article-id pub-id-type="doi">10.1371/journal.pgen.1001378</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline"><subject>Genetics and Genomics</subject><subject>Genetics and Genomics/Cancer Genetics</subject><subject>Genetics and Genomics/Complex Traits</subject><subject>Genetics and Genomics/Gene Discovery</subject><subject>Genetics and Genomics/Gene Expression</subject><subject>Genetics and Genomics/Genetics of Disease</subject><subject>Genetics and Genomics/Medical Genetics</subject><subject>Hematology</subject><subject>Hematology/Lymphomas and Chronic Lymphoblastic Leukemia</subject><subject>Oncology</subject><subject>Oncology/Hematological Malignancies</subject><subject>Oncology/Myelomas and Lymphoproliferative Diseases</subject></subj-group></article-categories><title-group><article-title>GWAS of Follicular Lymphoma Reveals Allelic Heterogeneity at 6p21.32
and Suggests Shared Genetic Susceptibility with Diffuse Large B-cell
Lymphoma</article-title><alt-title alt-title-type="running-head">Allelic Heterogeneity in Follicular
Lymphoma GWAS</alt-title></title-group><contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Smedby</surname><given-names>Karin E.</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Foo</surname><given-names>Jia Nee</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Skibola</surname><given-names>Christine F.</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="author-notes" rid="fn1"><sup>‡</sup></xref></contrib><contrib contrib-type="author"><name><surname>Darabi</surname><given-names>Hatef</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref><xref ref-type="author-notes" rid="fn1"><sup>‡</sup></xref></contrib><contrib contrib-type="author"><name><surname>Conde</surname><given-names>Lucia</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hjalgrim</surname><given-names>Henrik</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kumar</surname><given-names>Vikrant</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Chang</surname><given-names>Ellen T.</given-names></name><xref ref-type="aff" rid="aff6"><sup>6</sup></xref><xref ref-type="aff" rid="aff7"><sup>7</sup></xref></contrib><contrib contrib-type="author"><name><surname>Rothman</surname><given-names>Nathaniel</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Cerhan</surname><given-names>James R.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Brooks-Wilson</surname><given-names>Angela R.</given-names></name><xref ref-type="aff" rid="aff10"><sup>10</sup></xref><xref ref-type="aff" rid="aff11"><sup>11</sup></xref></contrib><contrib contrib-type="author"><name><surname>Rehnberg</surname><given-names>Emil</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Irwan</surname><given-names>Ishak D.</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ryder</surname><given-names>Lars P.</given-names></name><xref ref-type="aff" rid="aff12"><sup>12</sup></xref></contrib><contrib contrib-type="author"><name><surname>Brown</surname><given-names>Peter N.</given-names></name><xref ref-type="aff" rid="aff13"><sup>13</sup></xref></contrib><contrib contrib-type="author"><name><surname>Bracci</surname><given-names>Paige M.</given-names></name><xref ref-type="aff" rid="aff14"><sup>14</sup></xref></contrib><contrib contrib-type="author"><name><surname>Agana</surname><given-names>Luz</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Riby</surname><given-names>Jacques</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Cozen</surname><given-names>Wendy</given-names></name><xref ref-type="aff" rid="aff15"><sup>15</sup></xref></contrib><contrib contrib-type="author"><name><surname>Davis</surname><given-names>Scott</given-names></name><xref ref-type="aff" rid="aff16"><sup>16</sup></xref><xref ref-type="aff" rid="aff17"><sup>17</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hartge</surname><given-names>Patricia</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Morton</surname><given-names>Lindsay M.</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Severson</surname><given-names>Richard K.</given-names></name><xref ref-type="aff" rid="aff18"><sup>18</sup></xref><xref ref-type="aff" rid="aff19"><sup>19</sup></xref></contrib><contrib contrib-type="author"><name><surname>Wang</surname><given-names>Sophia S.</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref><xref ref-type="aff" rid="aff20"><sup>20</sup></xref></contrib><contrib contrib-type="author"><name><surname>Slager</surname><given-names>Susan L.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Fredericksen</surname><given-names>Zachary S.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Novak</surname><given-names>Anne J.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kay</surname><given-names>Neil E.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Habermann</surname><given-names>Thomas M.</given-names></name><xref ref-type="aff" rid="aff9"><sup>9</sup></xref></contrib><contrib contrib-type="author"><name><surname>Armstrong</surname><given-names>Bruce</given-names></name><xref ref-type="aff" rid="aff21"><sup>21</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kricker</surname><given-names>Anne</given-names></name><xref ref-type="aff" rid="aff21"><sup>21</sup></xref></contrib><contrib contrib-type="author"><name><surname>Milliken</surname><given-names>Sam</given-names></name><xref ref-type="aff" rid="aff22"><sup>22</sup></xref></contrib><contrib contrib-type="author"><name><surname>Purdue</surname><given-names>Mark P.</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Vajdic</surname><given-names>Claire M.</given-names></name><xref ref-type="aff" rid="aff23"><sup>23</sup></xref></contrib><contrib contrib-type="author"><name><surname>Boyle</surname><given-names>Peter</given-names></name><xref ref-type="aff" rid="aff24"><sup>24</sup></xref></contrib><contrib contrib-type="author"><name><surname>Lan</surname><given-names>Qing</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zahm</surname><given-names>Shelia H.</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Yawei</given-names></name><xref ref-type="aff" rid="aff25"><sup>25</sup></xref></contrib><contrib contrib-type="author"><name><surname>Zheng</surname><given-names>Tongzhang</given-names></name><xref ref-type="aff" rid="aff25"><sup>25</sup></xref></contrib><contrib contrib-type="author"><name><surname>Leach</surname><given-names>Stephen</given-names></name><xref ref-type="aff" rid="aff26"><sup>26</sup></xref></contrib><contrib contrib-type="author"><name><surname>Spinelli</surname><given-names>John J.</given-names></name><xref ref-type="aff" rid="aff10"><sup>10</sup></xref><xref ref-type="aff" rid="aff27"><sup>27</sup></xref></contrib><contrib contrib-type="author"><name><surname>Smith</surname><given-names>Martyn T.</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Chanock</surname><given-names>Stephen J.</given-names></name><xref ref-type="aff" rid="aff8"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Padyukov</surname><given-names>Leonid</given-names></name><xref ref-type="aff" rid="aff28"><sup>28</sup></xref></contrib><contrib contrib-type="author"><name><surname>Alfredsson</surname><given-names>Lars</given-names></name><xref ref-type="aff" rid="aff29"><sup>29</sup></xref></contrib><contrib contrib-type="author"><name><surname>Klareskog</surname><given-names>Lars</given-names></name><xref ref-type="aff" rid="aff28"><sup>28</sup></xref></contrib><contrib contrib-type="author"><name><surname>Glimelius</surname><given-names>Bengt</given-names></name><xref ref-type="aff" rid="aff30"><sup>30</sup></xref><xref ref-type="aff" rid="aff31"><sup>31</sup></xref></contrib><contrib contrib-type="author"><name><surname>Melbye</surname><given-names>Mads</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Liu</surname><given-names>Edison T.</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Adami</surname><given-names>Hans-Olov</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref><xref ref-type="aff" rid="aff32"><sup>32</sup></xref></contrib><contrib contrib-type="author"><name><surname>Humphreys</surname><given-names>Keith</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref><xref ref-type="author-notes" rid="fn2"><sup>¶</sup></xref></contrib><contrib contrib-type="author"><name><surname>Liu</surname><given-names>Jianjun</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref><xref ref-type="author-notes" rid="fn2"><sup>¶</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Department of Medicine, Clinical Epidemiology Unit, Karolinska Institutet, Stockholm, Sweden</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Human Genetics, Genome Institute of Singapore, A*STAR, Singapore, Singapore</addr-line></aff><aff id="aff3"><label>3</label><addr-line>Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, United States of America</addr-line></aff><aff id="aff4"><label>4</label><addr-line>Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden</addr-line></aff><aff id="aff5"><label>5</label><addr-line>Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark</addr-line></aff><aff id="aff6"><label>6</label><addr-line>Cancer Prevention Institute of California, Fremont, California, United States of America</addr-line></aff><aff id="aff7"><label>7</label><addr-line>Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America</addr-line></aff><aff id="aff8"><label>8</label><addr-line>Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></aff><aff id="aff9"><label>9</label><addr-line>College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America</addr-line></aff><aff id="aff10"><label>10</label><addr-line>British Columbia Cancer Research Center, British Columbia Cancer Agency, Vancouver, Canada</addr-line></aff><aff id="aff11"><label>11</label><addr-line>Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, Canada</addr-line></aff><aff id="aff12"><label>12</label><addr-line>Department of Clinical Immunology, University Hospital of Copenhagen, Copenhagen, Denmark</addr-line></aff><aff id="aff13"><label>13</label><addr-line>Department of Haematology, Copenhagen University Hospital, Copenhagen, Denmark</addr-line></aff><aff id="aff14"><label>14</label><addr-line>Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America</addr-line></aff><aff id="aff15"><label>15</label><addr-line>Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America</addr-line></aff><aff id="aff16"><label>16</label><addr-line>Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America</addr-line></aff><aff id="aff17"><label>17</label><addr-line>University of Washington, Seattle, Washington, United States of America</addr-line></aff><aff id="aff18"><label>18</label><addr-line>Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, Michigan, United States of America</addr-line></aff><aff id="aff19"><label>19</label><addr-line>Karmanos Cancer Institute, Detroit, Michigan, United States of America</addr-line></aff><aff id="aff20"><label>20</label><addr-line>Division of Etiology, Beckman Research Institute and the City of Hope, Duarte, California, United States of America</addr-line></aff><aff id="aff21"><label>21</label><addr-line>Sydney School of Public Health, The University of Sydney, Sydney, Australia</addr-line></aff><aff id="aff22"><label>22</label><addr-line>Department of Haematology, St. Vincent's Hospital, Sydney, Australia</addr-line></aff><aff id="aff23"><label>23</label><addr-line>University of New South Wales Cancer Research Center, Prince of Wales Clinical School, Sydney, Australia</addr-line></aff><aff id="aff24"><label>24</label><addr-line>International Prevention Research Institute, Lyon, France</addr-line></aff><aff id="aff25"><label>25</label><addr-line>School of Public Health, Yale University, New Haven, Connecticut, United States of America</addr-line></aff><aff id="aff26"><label>26</label><addr-line>Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, Canada</addr-line></aff><aff id="aff27"><label>27</label><addr-line>School of Population and Public Health, University of British Columbia, Vancouver, Canada</addr-line></aff><aff id="aff28"><label>28</label><addr-line>Rheumatology Unit, Department of Medicine, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden</addr-line></aff><aff id="aff29"><label>29</label><addr-line>Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden</addr-line></aff><aff id="aff30"><label>30</label><addr-line>Department of Pathology and Oncology, Karolinska Institutet, Stockholm, Sweden</addr-line></aff><aff id="aff31"><label>31</label><addr-line>Department of Radiology, Oncology, and Radiation Sciences, Uppsala University, Uppsala, Sweden</addr-line></aff><aff id="aff32"><label>32</label><addr-line>Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Gibson</surname><given-names>Greg</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1">Georgia Institute of Technology, United States of America</aff><author-notes><corresp id="cor1">* E-mail: <email>liuj3@gis.a-star.edu.sg</email></corresp><fn fn-type="con"><p>Conceived and designed the experiments: KES ETL HOA JL. Performed the
experiments: IDI. Analyzed the data: KES JNF CFS HD LC VK ER KH JL.
Contributed reagents/materials/analysis tools: KES CFS LC HH ETC NR JRC LPR
PNB PMB LA JR WC SD PH LMM RKS SSW SLS ZSF AJN NEK TMH BA AK SM MPP CMV PB
QL SHZ YZ TZ SL JJS MTS SJC LP LA LK BG MM ETL HOA JL. Wrote the paper: KES
JNF KH JL. Critical revision of manuscript: CFS HD LC VK ETC IDI SJC.
Genotyped samples and provided data from the BC study: ARBW. Provided data
from the SF1 and SF2 GWAS studies: JR. Supervised the experiments: JL
JNF.</p></fn><fn id="fn1" fn-type="other"><p>‡ These authors also contributed equally to this work.</p></fn><fn id="fn2" fn-type="other"><p>¶ These authors also contributed equally to this work.</p></fn></author-notes><pub-date pub-type="collection"><month>4</month><year>2011</year></pub-date><pub-date pub-type="epub"><day>21</day><month>4</month><year>2011</year></pub-date><volume>7</volume><issue>4</issue><elocation-id>e1001378</elocation-id><history><date date-type="received"><day>24</day><month>9</month><year>2010</year></date><date date-type="accepted"><day>18</day><month>3</month><year>2011</year></date></history><permissions><copyright-statement>This is an open-access article, free of all copyright, and may be
freely reproduced, distributed, transmitted, modified, built upon, or otherwise used
by anyone for any lawful purpose. The work is made available under the Creative
Commons CC0 public domain dedication.</copyright-statement><copyright-year>2011</copyright-year><license xlink:href="https://creativecommons.org/publicdomain/zero/1.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.</license-p></license></permissions><abstract><p>Non-Hodgkin lymphoma (NHL) represents a diverse group of hematological
malignancies, of which follicular lymphoma (FL) is a prevalent subtype. A
previous genome-wide association study has established a marker, rs10484561 in
the human leukocyte antigen (HLA) class II region on 6p21.32 associated with
increased FL risk. Here, in a three-stage genome-wide association study,
starting with a genome-wide scan of 379 FL cases and 791 controls followed by
validation in 1,049 cases and 5,790 controls, we identified a second independent
FL–associated locus on 6p21.32, rs2647012
(OR<sub>combined</sub> = 0.64,
P<sub>combined</sub> = 2×10<sup>−21</sup>)
located 962 bp away from rs10484561 (r<sup>2</sup><0.1 in controls). After
mutual adjustment, the associations at the two SNPs remained genome-wide
significant (rs2647012:OR<sub>adjusted</sub> = 0.70,
P<sub>adjusted</sub> = 4×10<sup>−12</sup>;
rs10484561:OR<sub>adjusted</sub> = 1.64,
P<sub>adjusted</sub> = 5×10<sup>−15</sup>).
Haplotype and coalescence analyses indicated that rs2647012 arose on an
evolutionarily distinct haplotype from that of rs10484561 and tags a novel
allele with an opposite (protective) effect on FL risk. Moreover, in a follow-up
analysis of the top 6 FL–associated SNPs in 4,449 cases of other NHL
subtypes, rs10484561 was associated with risk of diffuse large B-cell lymphoma
(OR<sub>combined</sub> = 1.36,
P<sub>combined</sub> = 1.4×10<sup>−7</sup>).
Our results reveal the presence of allelic heterogeneity within the HLA class II
region influencing FL susceptibility and indicate a possible shared genetic
etiology with diffuse large B-cell lymphoma. These findings suggest that the HLA
class II region plays a complex yet important role in NHL.</p></abstract><abstract abstract-type="summary"><title>Author Summary</title><p>Earlier studies have established a marker rs10484561, in the HLA class II region
on 6p21.32, associated with increased follicular lymphoma (FL) risk. Here, in a
three-stage genome-wide association study of 1,428 FL cases and 6,581 controls,
we identified a second independent FL–associated marker on 6p21.32,
rs2647012, located 962 bp away from rs10484561. The associations at two SNPs
remained genome-wide significant after mutual adjustment. Haplotype and
coalescence analyses indicated that rs2647012 arose on an evolutionarily
distinct lineage from that of rs10484561 and tags a novel allele with an
opposite, protective effect on FL risk. Moreover, in an analysis of the top 6
FL–associated SNPs in 4,449 cases of other NHL subtypes, rs10484561 was
associated with risk of diffuse large B-cell lymphoma. Our results reveal the
presence of allelic heterogeneity at 6p21.32 in FL risk and suggest a shared
genetic etiology with the common diffuse large B-cell lymphoma subtype.</p></abstract><counts><page-count count="11"></page-count></counts></article-meta></front><body><sec id="s1"><title>Introduction</title><p>Non-Hodgkin lymphoma (NHL) represents a diverse group of B- and T-cell malignancies
of lymphatic origin. The most common subtypes are of B-cell origin and are further
classified on the basis of their resemblance to normal stages of B-cell
differentiation <xref rid="pgen.1001378-Jaffe1" ref-type="bibr">[1]</xref>. Epidemiological studies indicate that these may have
different environmental and genetic risk factors, although some etiological factors
may also be shared <xref rid="pgen.1001378-Morton1" ref-type="bibr">[2]</xref>. Familial studies provide substantial evidence for a
genetic influence on susceptibility to the major mature B-cell neoplasms, including
diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and chronic
lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) <xref rid="pgen.1001378-Altieri1" ref-type="bibr">[3]</xref>, <xref rid="pgen.1001378-Chang1" ref-type="bibr">[4]</xref>. Recent genome-wide association
studies (GWAS) of the FL subtype of NHL identified associations with two variants
within the human leukocyte antigen (HLA) region, one at 6p21.33 (rs6457327) <xref rid="pgen.1001378-Skibola1" ref-type="bibr">[5]</xref> and the other
at 6p21.32 (rs10484561) <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. Additional true associations, particularly in the HLA
region, may have been missed because a limited number of samples were used in the
initial genome-wide screens, and the selection of a few top single nucleotide
polymorphisms (SNPs) for validation is further subject to chance. In this study, we
conducted a larger independent genome-wide scan of FL using 379 cases and 791
controls from the Scandinavian Lymphoma Etiology (SCALE) study of Sweden and
Denmark, which was used in the validation of the previous GWAS <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. This scan was followed by two
stages of validation in European-ancestry cases of FL and other common B-cell NHL
subtypes and controls from the US, Canada and Australia (<xref ref-type="table" rid="pgen-1001378-t001">Table 1</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s007">Table S1</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s008">Table S2</xref>, <xref ref-type="fig" rid="pgen-1001378-g001">Figure 1</xref>).</p><fig id="pgen-1001378-g001" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.g001</object-id><label>Figure 1</label><caption><title>Schematic representation of the three-stage study design.</title><p>Summary of contributing studies and number of samples per case/control
status. Abbreviations: FL: follicular lymphoma, NHL: non-Hodgkin lymphoma,
DLBCL: diffuse large B-cell lymphoma, CLL/SLL: chronic lymphocytic
leukemia/small lymphocytic lymphoma, SNP: single nucleotide polymorphism,
GWAS: genome-wide association study, SCALE: Scandinavian lymphoma etiology,
SF: San Francisco, BC: British Columbia, NCI-SEER: National Cancer
Institute-Surveillance, Epidemiology and End Results, NSW: New South Wales,
Yale: Yale University, Mayo: Mayo Clinic. The complete list of the number of
other NHL subtypes in each study is detailed in <xref ref-type="supplementary-material" rid="pgen.1001378.s007">Table
S1</xref>.</p></caption><graphic xlink:href="pgen.1001378.g001"></graphic></fig><table-wrap id="pgen-1001378-t001" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.t001</object-id><label>Table 1</label><caption><title>Summary of contributing studies, genotyping methods, and number of
samples per case/control status.</title></caption><alternatives><graphic id="pgen-1001378-t001-1" xlink:href="pgen.1001378.t001"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td align="left" rowspan="1" colspan="1">Stage</td><td align="left" rowspan="1" colspan="1">Study</td><td align="left" rowspan="1" colspan="1">Population</td><td align="left" rowspan="1" colspan="1">Genotyping method</td><td align="left" rowspan="1" colspan="1">Controls</td><td align="left" rowspan="1" colspan="1">FL</td><td align="left" rowspan="1" colspan="1">Other NHL subtypes<xref ref-type="table-fn" rid="nt102">*</xref></td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">1</td><td align="left" rowspan="1" colspan="1">SCALE1</td><td align="left" rowspan="1" colspan="1">Denmark/Sweden</td><td align="left" rowspan="1" colspan="1">Illumina 317k</td><td align="left" rowspan="1" colspan="1">791</td><td align="left" rowspan="1" colspan="1">379</td><td align="left" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1">2</td><td align="left" rowspan="1" colspan="1">SF1</td><td align="left" rowspan="1" colspan="1">San Francisco Bay Area, USA</td><td align="left" rowspan="1" colspan="1">Illumina HumanCNV370-Duo Beadchip</td><td align="left" rowspan="1" colspan="1">750</td><td align="left" rowspan="1" colspan="1">213</td><td align="left" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1">3/subtype validation</td><td align="left" rowspan="1" colspan="1">NCI-SEER</td><td align="left" rowspan="1" colspan="1">USA</td><td align="left" rowspan="1" colspan="1">Taqman</td><td align="left" rowspan="1" colspan="1">501</td><td align="left" rowspan="1" colspan="1">157</td><td align="left" rowspan="1" colspan="1">468</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">NSW</td><td align="left" rowspan="1" colspan="1">New South Wales, Australia</td><td align="left" rowspan="1" colspan="1">Taqman</td><td align="left" rowspan="1" colspan="1">398</td><td align="left" rowspan="1" colspan="1">161</td><td align="left" rowspan="1" colspan="1">261</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">Yale</td><td align="left" rowspan="1" colspan="1">USA</td><td align="left" rowspan="1" colspan="1">Taqman</td><td align="left" rowspan="1" colspan="1">460</td><td align="left" rowspan="1" colspan="1">98</td><td align="left" rowspan="1" colspan="1">300</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">BC</td><td align="left" rowspan="1" colspan="1">British Columbia, Canada</td><td align="left" rowspan="1" colspan="1">Taqman</td><td align="left" rowspan="1" colspan="1">610</td><td align="left" rowspan="1" colspan="1">174</td><td align="left" rowspan="1" colspan="1">451</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">Mayo</td><td align="left" rowspan="1" colspan="1">Minnesota, Iowa, Wisconsin, USA</td><td align="left" rowspan="1" colspan="1">OPA</td><td align="left" rowspan="1" colspan="1">1233</td><td align="left" rowspan="1" colspan="1">246</td><td align="left" rowspan="1" colspan="1">843</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">SCALE2</td><td align="left" rowspan="1" colspan="1">Denmark/Sweden</td><td align="left" rowspan="1" colspan="1">Sequenom/Taqman</td><td align="left" rowspan="1" colspan="1">2018</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">1869</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">SF2</td><td align="left" rowspan="1" colspan="1">San Francisco Bay Area, USA</td><td align="left" rowspan="1" colspan="1">Illumina HumanCNV370-Duo Beadchip</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">257</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Total</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"><bold>6761</bold></td><td align="left" rowspan="1" colspan="1"><bold>1428</bold></td><td align="left" rowspan="1" colspan="1"><bold>4449</bold></td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt101"><label></label><p>Abbreviations: SCALE: Scandinavian lymphoma etiology, SF: San Francisco,
NCI-SEER: National Cancer Institute- Surveillance, Epidemiology and End
Results, NSW: New South Wales, Yale: Yale University, BC: British
Columbia, Mayo: Mayo Clinic, OPA: oligonucleotuide pool assays (Illumina
GoldenGate).</p></fn><fn id="nt102"><label></label><p>*The complete list of the number of other NHL subtypes in each study
is detailed in <xref ref-type="supplementary-material" rid="pgen.1001378.s007">Table S1</xref>.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s2"><title>Results</title><p>In total, 298,168 SNPs were analyzed in Stage 1 (λ = 1.028;
λ<sub>1000</sub> = 1.055 <xref rid="pgen.1001378-deBakker1" ref-type="bibr">[7]</xref>), in which we observed
suggestive associations (adjusted trend P-value<10<sup>−5</sup>) at 4q32.3,
6p21.32 and 10q25.3 (<xref ref-type="supplementary-material" rid="pgen.1001378.s009">Table S3</xref>) with the strongest at rs2647012 (odds ratio
(OR) = 0.58, P<sub>PCAadjusted</sub> =
1.59x10<sup>−7</sup>) within the HLA class II region on 6p21.32. Sixteen
SNPs in close proximity to the <italic>HLA-DQ</italic> genes showed association with
adjusted P-values<10<sup>−4</sup>, including the previously reported
rs10484561 (<xref ref-type="fig" rid="pgen-1001378-g002">Figure 2</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s010">Table S4</xref>) <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. The previously
reported HLA class I associated SNP rs6457327 <xref rid="pgen.1001378-Skibola1" ref-type="bibr">[5]</xref> was modestly associated with FL
risk (OR = 0.82, P = 0.03) in Stage 1, and
was not in linkage disequilibrium (LD; r<sup>2</sup> = 0) with
any of the top 100 SNPs.</p><p>In Stage 2, we carried out an <italic>in silico</italic> validation of the top 40
SNPs from Stage 1 (<xref ref-type="supplementary-material" rid="pgen.1001378.s011">Table S5</xref>) in 213 FL cases and 750 controls from the San Francisco Bay
Area, USA (<xref ref-type="table" rid="pgen-1001378-t001">Table 1</xref>), the study
that reported an association at 6p21.32 <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. Among 38 out of 40 SNPs, seven
showed association (P<0.05) in Stage 2 (<xref ref-type="supplementary-material" rid="pgen.1001378.s011">Table S5</xref>), six of which were located within the
6p21.32 region. We tested the independence of multiple association signals in
6p21.32 using a stepwise logistic regression analysis (entering SNPs based on a
criterion of likelihood ratio test p-value<0.05) and found that with rs2647012
(the top SNP within the region) forced in the model, only the addition of rs10484561
contributed significantly to the association with increased risk of FL. The OR for
this SNP, adjusted for rs2647012, was 1.43, P = 0.006 (<xref ref-type="supplementary-material" rid="pgen.1001378.s012">Table S6</xref>).</p><fig id="pgen-1001378-g002" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.g002</object-id><label>Figure 2</label><caption><title>Recombination plot showing associations in 6p21.32 in Stage 1.</title><p>Plot showing the pattern of associations in Stage 1, the recombination rate
(build 36, HapMap CEU) and genes located in the region. The two SNPs showing
independent association and their respective P-values are labeled (blue:
rs2647012, green: rs10484561); other SNPs are color-coded according to their
LD with rs2647012 (red r<sup>2</sup>>0.8, orange 0.5–0.8, grey
0.2–0.5, white <0.2).</p></caption><graphic xlink:href="pgen.1001378.g002"></graphic></fig><p>After excluding previously identified and non-independent association signals, we
selected rs2647012, and an additional four top SNPs to be taken forward to a third
stage (<xref ref-type="supplementary-material" rid="pgen.1001378.s013">Table
S7</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s014">S8</xref>), wherein these were genotyped in 836 FL cases and 3202 controls from
the Mayo Clinic (US) <xref rid="pgen.1001378-Cerhan1" ref-type="bibr">[8]</xref>, National Cancer Institute-Surveillance, Epidemiology and
End Results (NCI-SEER, US) <xref rid="pgen.1001378-Wang1" ref-type="bibr">[9]</xref>, Yale University (US) <xref rid="pgen.1001378-Zhang1" ref-type="bibr">[10]</xref>, New South Wales (NSW,
Australia) <xref rid="pgen.1001378-Hughes1" ref-type="bibr">[11]</xref>and British Columbia (BC, Canada) <xref rid="pgen.1001378-Spinelli1" ref-type="bibr">[12]</xref> studies. The association of rs2647012 with FL was
validated, showing consistent associations with similar ORs (no heterogeneity,
P = 0.32) across all independent studies and reaching
genome-wide significance in both the combined analysis of the validation samples
(P = 3×10<sup>−15</sup>) and the combined
analysis of all three stages (1428 FL cases, 4743 controls;
OR = 0.64,
P = 2×10<sup>−21</sup>) (<xref ref-type="table" rid="pgen-1001378-t002">Table.2</xref>, <xref ref-type="fig" rid="pgen-1001378-g003">Figure 3</xref>). After adjustment for rs10484561, the
association at rs2647012 remained genome-wide significant with minimal change in
magnitude (OR<sub>adjusted</sub> = 0.70,
P<sub>adjusted</sub> = 4×10<sup>−12</sup>). The
LD between the two SNPs is low (r<sup>2</sup><0.1 in the SCALE controls and
HapMap CEU [Utah residents with northern and western European ancestry]
samples release27). Taken together, our results suggest that the association at
rs2647012 is independent from rs10484561, and tags a different disease-predisposing
variant. We also found suggestive evidence for an association at rs6536942 on 4q32.3
(OR = 1.36,
P = 2×10<sup>−5</sup>) (<xref ref-type="table" rid="pgen-1001378-t002">Table 2</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s001">Figure S1A</xref>).</p><fig id="pgen-1001378-g003" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.g003</object-id><label>Figure 3</label><caption><title>Forest plots of main associations with risk of FL.</title><p>Forest plots showing the associations in each study (ORs and P-values) at
rs2647012 before adjustment
(P<sub>heterogeneity</sub> = 0.32), and at rs2647012
(P<sub>heterogeneity</sub> = 0.67) and rs10484561
(P<sub>heterogeneity</sub> = 0.54) after mutual
adjustment. Squares indicate the odds ratios, with the size proportional to
the weight of the study in the meta-analysis. Abbreviations: CI: confidence
interval, SCALE: Scandinavian lymphoma etiology, SF: San Francisco, BC:
British Columbia, NCI: National Cancer Institute-Surveillance, Epidemiology
and End Results, NSW: New South Wales, YALE: Yale University, MAYO: Mayo
Clinic.</p></caption><graphic xlink:href="pgen.1001378.g003"></graphic></fig><table-wrap id="pgen-1001378-t002" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.t002</object-id><label>Table 2</label><caption><title>Summary of main findings in genome-wide association study (GWAS) and
validation stages in risk<xref ref-type="table-fn" rid="nt103">*</xref>of follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), or
marginal zone lymphoma (MZL), per study and combined.</title></caption><alternatives><graphic id="pgen-1001378-t002-2" xlink:href="pgen.1001378.t002"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td align="left" rowspan="1" colspan="1"></td><td colspan="4" align="left" rowspan="1">FL</td><td align="left" rowspan="1" colspan="1">DLBCL</td><td align="left" rowspan="1" colspan="1">MZL</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">rs2647012</td><td align="left" rowspan="1" colspan="1">rs2647012adj for rs10484561<xref ref-type="table-fn" rid="nt104">**</xref></td><td align="left" rowspan="1" colspan="1">rs10484561adj for rs2647012<xref ref-type="table-fn" rid="nt104">**</xref></td><td align="left" rowspan="1" colspan="1">rs6536942</td><td align="left" rowspan="1" colspan="1">rs10484561</td><td align="left" rowspan="1" colspan="1">rs2647012</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">chr6:32772436 <italic>HLA-DQB1</italic></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">chr4:167205644 <italic>TLL1</italic></td><td align="left" rowspan="1" colspan="1">chr6:32773398 <italic>HLA-DQB1</italic></td><td align="left" rowspan="1" colspan="1">chr6:32772436 <italic>HLA-DQB1</italic></td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>Stage 1</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">SCALE1</td><td align="left" rowspan="1" colspan="1">1×10<sup>−7</sup></td><td align="left" rowspan="1" colspan="1">1×10<sup>−5</sup></td><td align="left" rowspan="1" colspan="1">0.006</td><td align="left" rowspan="1" colspan="1">1×10<sup>−6</sup></td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.60 (0.50–0.73)</td><td align="left" rowspan="1" colspan="1">0.65 (0.53–0.79)</td><td align="left" rowspan="1" colspan="1">1.43 (1.11–1.84)</td><td align="left" rowspan="1" colspan="1">1.86 (1.45–2.34)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Stage 2</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">SF</td><td align="left" rowspan="1" colspan="1">0.005</td><td align="left" rowspan="1" colspan="1">0.08</td><td align="left" rowspan="1" colspan="1">0.002</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.72 (0.57–0.91)</td><td align="left" rowspan="1" colspan="1">0.80 (0.62–1.03)</td><td align="left" rowspan="1" colspan="1">1.60 (1.19–2.16)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1.36 (1.05–1.80)</td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Stage 3</bold></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">BC</td><td align="left" rowspan="1" colspan="1">0.004</td><td align="left" rowspan="1" colspan="1">0.06</td><td align="left" rowspan="1" colspan="1">3×10<sup>−5</sup></td><td align="left" rowspan="1" colspan="1">0.72</td><td align="left" rowspan="1" colspan="1">0.001</td><td align="left" rowspan="1" colspan="1">0.01</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.69 (0.53–0.89)</td><td align="left" rowspan="1" colspan="1">0.77 (0.58–1.01)</td><td align="left" rowspan="1" colspan="1">2.06 (1.46–2.90)</td><td align="left" rowspan="1" colspan="1">1.08 (0.72–1.61)</td><td align="left" rowspan="1" colspan="1">1.77 (1.26–2.48)</td><td align="left" rowspan="1" colspan="1">1.56 (1.10–2.22)</td></tr><tr><td align="left" rowspan="1" colspan="1">NCI-SEER</td><td align="left" rowspan="1" colspan="1">0.12</td><td align="left" rowspan="1" colspan="1">0.17</td><td align="left" rowspan="1" colspan="1">0.08</td><td align="left" rowspan="1" colspan="1">0.13</td><td align="left" rowspan="1" colspan="1">0.15</td><td align="left" rowspan="1" colspan="1">0.06</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.81 (0.61–1.06)</td><td align="left" rowspan="1" colspan="1">0.81 (0.59–1.10)</td><td align="left" rowspan="1" colspan="1">1.41 (0.96–2.08)</td><td align="left" rowspan="1" colspan="1">1.34 (0.92–1.95)</td><td align="left" rowspan="1" colspan="1">1.32 (0.90–1.94)</td><td align="left" rowspan="1" colspan="1">1.51 (0.99–2.31)</td></tr><tr><td align="left" rowspan="1" colspan="1">NSW</td><td align="left" rowspan="1" colspan="1">1×10<sup>−4</sup></td><td align="left" rowspan="1" colspan="1">0.05</td><td align="left" rowspan="1" colspan="1">0.006</td><td align="left" rowspan="1" colspan="1">0.42</td><td align="left" rowspan="1" colspan="1">0.01</td><td align="left" rowspan="1" colspan="1">0.45</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.53 (0.38–0.73)</td><td align="left" rowspan="1" colspan="1">0.69 (0.48–1.01)</td><td align="left" rowspan="1" colspan="1">1.94 (1.21–3.11)</td><td align="left" rowspan="1" colspan="1">1.21 (0.76–1.91)</td><td align="left" rowspan="1" colspan="1">1.74 (1.12–2.72)</td><td align="left" rowspan="1" colspan="1">1.23 (0.72–2.08)</td></tr><tr><td align="left" rowspan="1" colspan="1">Yale</td><td align="left" rowspan="1" colspan="1">0.008</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">0.14</td><td align="left" rowspan="1" colspan="1">0.74</td><td align="left" rowspan="1" colspan="1">0.40</td><td align="left" rowspan="1" colspan="1">0.73</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.63 (0.45–0.89)</td><td align="left" rowspan="1" colspan="1">0.69 (0.48–0.99)</td><td align="left" rowspan="1" colspan="1">1.38 (0.90–2.12)</td><td align="left" rowspan="1" colspan="1">1.08 (0.67–1.74)</td><td align="left" rowspan="1" colspan="1">1.18 (0.79–1.77)</td><td align="left" rowspan="1" colspan="1">1.10 (0.63–1.92)</td></tr><tr><td align="left" rowspan="1" colspan="1">Mayo</td><td align="left" rowspan="1" colspan="1">1×10<sup>−7</sup></td><td align="left" rowspan="1" colspan="1">1×10<sup>−4</sup></td><td align="left" rowspan="1" colspan="1">0.28</td><td align="left" rowspan="1" colspan="1">0.28</td><td align="left" rowspan="1" colspan="1">0.01</td><td align="left" rowspan="1" colspan="1">0.38</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.56 (0.45–0.69)</td><td align="left" rowspan="1" colspan="1">0.64 (0.51–0.80)</td><td align="left" rowspan="1" colspan="1">1.17 (1.45–2.53)</td><td align="left" rowspan="1" colspan="1">1.17 (0.88–1.56)</td><td align="left" rowspan="1" colspan="1">1.52 (1.11–2.08)</td><td align="left" rowspan="1" colspan="1">1.18 (0.82–1.69)</td></tr><tr><td align="left" rowspan="1" colspan="1">SCALE2</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">0.08</td><td align="left" rowspan="1" colspan="1">0.10</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1.19 (0.98–1.44)</td><td align="left" rowspan="1" colspan="1">1.29 (0.95–1.74)</td></tr><tr><td align="left" rowspan="1" colspan="1">Joint</td><td align="left" rowspan="1" colspan="1">3×10<sup>−15</sup></td><td align="left" rowspan="1" colspan="1">6×10<sup>−8</sup></td><td align="left" rowspan="1" colspan="1">9×10<sup>−14</sup></td><td align="left" rowspan="1" colspan="1">0.06</td><td align="left" rowspan="1" colspan="1">-</td><td align="left" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.65 (0.58–0.72)</td><td align="left" rowspan="1" colspan="1">0.73 (0.65–0.82)</td><td align="left" rowspan="1" colspan="1">1.72 (1.49–1.98)</td><td align="left" rowspan="1" colspan="1">1.18 (1.00–1.40)</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>All</bold> (Stages 1,2,3)</td><td align="left" rowspan="1" colspan="1">2×10<sup>−21</sup></td><td align="left" rowspan="1" colspan="1">4×10<sup>−12</sup></td><td align="left" rowspan="1" colspan="1">5×10<sup>−15</sup></td><td align="left" rowspan="1" colspan="1">2×10<sup>−5</sup></td><td align="left" rowspan="1" colspan="1">1×10<sup>−7</sup></td><td align="left" rowspan="1" colspan="1">6×10<sup>−4</sup></td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">0.64 (0.58–0.70)</td><td align="left" rowspan="1" colspan="1">0.70 (0.67–0.78)</td><td align="left" rowspan="1" colspan="1">1.64 (1.45–1.86)</td><td align="left" rowspan="1" colspan="1">1.36 (1.18–1.56)</td><td align="left" rowspan="1" colspan="1">1.36 (1.21–1.52)</td><td align="left" rowspan="1" colspan="1">1.32 (1.13–1.55)</td></tr><tr><td align="left" rowspan="1" colspan="1">P<sub>heterogeneity</sub><xref ref-type="table-fn" rid="nt105">†</xref></td><td align="left" rowspan="1" colspan="1">0.32</td><td align="left" rowspan="1" colspan="1">0.67</td><td align="left" rowspan="1" colspan="1">0.54</td><td align="left" rowspan="1" colspan="1">0.09</td><td align="left" rowspan="1" colspan="1">0.28</td><td align="left" rowspan="1" colspan="1">0.83</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt103"><label></label><p>*The trend test P-value for each study is shown with the
corresponding odds ratios (OR) and confidence interval (CI) below.</p></fn><fn id="nt104"><label></label><p>**Additional adjustment for rs6457327, rs4947332, rs1794265,
rs1800629, rs2517448 did not confer other than marginal changes.</p></fn><fn id="nt105"><label></label><p>†Test of heterogeneity carried out assuming heterogeneity of
effect of the “other” SNP.</p></fn><fn id="nt106"><label></label><p>SCALE: Scandinavian Lymphoma Etiology; SF: San Francisco; BC: British
Columbia; NCI-SEER: National Cancer Institute-Surveillance, Epidemiology
and End Results; NSW: New South Wales.</p></fn></table-wrap-foot></table-wrap><p>To fine-map the association signals in the HLA class II region, we imputed 10,639
SNPs within 600 kb surrounding the top SNP rs2647012 using data from the 1000
Genomes (1000G, 60 CEU subjects, August 2009) and HapMap projects (HapMapII release
22, CEU) in Stage 1. Among the imputed SNPs, 258 SNPs located in a strong LD block
of 236 kb (r<sup>2</sup>>0.8) showed stronger evidence of association than all
the genotyped SNPs within the region (<xref ref-type="supplementary-material" rid="pgen.1001378.s002">Figure S2</xref>). Since a moderate discordance of
reference genotypes was observed between 1000 G and HapMapII, we analyzed only SNPs
showing a concordance of >95% in the two datasets and identified the
strongest association at rs9378212 (OR = 1.66,
P = 3.21×10<sup>−8</sup>), located 219 kb
upstream of rs2647012 (r<sup>2</sup> = 0.56 in controls). We
subsequently confirmed the imputed genotypes by Taqman genotyping in 345 of the FL
case subjects used in Stage 1 and found a 99.4% concordance with the imputed
genotypes, demonstrating high confidence in the results of the imputation.</p><p>Next, we performed a haplotype analysis using rs2647012, rs10484561 and an additional
12 adjacent genotyped SNPs located within a block of minimal recombination. Out of
the eight haplotypes identified, three were neutral
(OR = 0.9–1.1), three increased risk (ORs>1.2;
strongest risk haplotype tagged by rs10484561) and two were protective (OR≤0.8;
both tagged by rs2647012) (<xref ref-type="supplementary-material" rid="pgen.1001378.s015">Table S9</xref>), suggesting the presence of at least
two susceptibility alleles within the region. Coalescence analysis of the eight
haplotypes indicated that rs2647012 and rs10484561 arose on two distal branches of
the ancestral recombination graph <xref rid="pgen.1001378-Song1" ref-type="bibr">[13]</xref> (<xref ref-type="supplementary-material" rid="pgen.1001378.s003">Figure S3</xref>), which was also supported by the
analysis of median-joining network <xref rid="pgen.1001378-Bandelt1" ref-type="bibr">[14]</xref> using seven SNPs without any recombination (<xref ref-type="fig" rid="pgen-1001378-g004">Figure 4</xref>). Further haplotype
analysis of the seven genotyped SNPs (<xref ref-type="supplementary-material" rid="pgen.1001378.s015">Table S9</xref>) and the imputed SNP rs9378212 indicated
that the two alleles of rs9378212 tag the two different evolutionary lineages (<xref ref-type="fig" rid="pgen-1001378-g004">Figure 4</xref>), each harboring either
rs2647012 or rs10484561. Thus, the associations at the two SNPs are likely due to
two distinct susceptibility variants, instead of a single risk allele, that arose
independently on different haplotype backgrounds.</p><fig id="pgen-1001378-g004" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.g004</object-id><label>Figure 4</label><caption><title>Coalescence analysis of rs2647012 and rs10484561.</title><p>Median-joining network <xref rid="pgen.1001378-Bandelt1" ref-type="bibr">[14]</xref> of haplotypes constructed using seven SNPs (<xref ref-type="supplementary-material" rid="pgen.1001378.s015">Table
S9</xref>). Circles represent haplotypes with area proportional to their
frequency. SNPs are shown on the links (black lines). SNPs and haplotypes
associated with increased or decreased FL risk are labeled in red or blue,
respectively. The percentage of alleles of the imputed SNP rs9378212 (C/T)
phased on each haplotype are shown in bold.</p></caption><graphic xlink:href="pgen.1001378.g004"></graphic></fig><p>The FL-associated SNP, rs10484561, was previously found to tag the extended haplotype
<italic>HLA-DQA1*0101-HLA-DQB1*0501-HLA-DRB1*0101</italic><xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. Here, to test
whether any HLA class II alleles may also be responsible for the observed
association at rs2647012, we imputed known HLA tag SNPs <xref rid="pgen.1001378-deBakker2" ref-type="bibr">[15]</xref>, <xref rid="pgen.1001378-Leslie1" ref-type="bibr">[16]</xref> using data from the 1000G and
HapMapII European datasets. We confirmed the association of the
<italic>HLA-DRB1*0101-HLA-DQA1*0101-HLA-DQB1*0501</italic> extended
haplotype, tagged by rs10484561. The association at rs2647012 remained significant
after adjustment for these three HLA alleles (OR = 0.64,
P = 8.11×10<sup>−6</sup>), suggesting that
these are not driving the association at rs2647012. Furthermore, rs2647012 was not
in strong LD (r<sup>2</sup><0.8 in HapMap CEU or SCALE controls) with any other
known HLA tags <xref rid="pgen.1001378-deBakker2" ref-type="bibr">[15]</xref>, including those tagging FL-associated alleles previously
reported <xref rid="pgen.1001378-Wang2" ref-type="bibr">[17]</xref>, <xref rid="pgen.1001378-Abdou1" ref-type="bibr">[18]</xref>(r<sup>2</sup><0.39 with the six <italic>HLA-DRB1*13</italic> tag SNPs
[rs2395173, rs2157051, rs4434496, rs6901541, rs424232, rs2050191] <xref rid="pgen.1001378-Wang2" ref-type="bibr">[17]</xref> and
r<sup>2</sup><0.25 with the three <italic>HLA-B*0801</italic> and
<italic>HLA-DRB*0301</italic> tag SNPs [rs6457374, rs2844535,
rs2040410] <xref rid="pgen.1001378-deBakker2" ref-type="bibr">[15]</xref>). Of the other 17 HLA class II alleles (∼39%
of all the class II alleles) that could be imputed, none showed significant
association or were found to be responsible for the association at rs2647012 (<xref ref-type="supplementary-material" rid="pgen.1001378.s016">Table S10</xref>).
Detailed HLA allelotyping on large numbers of cases and controls is needed to
determine if particular HLA class II alleles are responsible for the observed
association at rs2647012.</p><p>To assess whether the FL-associated SNPs may be involved in the development of other
NHL subtypes, we genotyped the five SNPs selected for Stage 3 together with
rs10484561 in a total of 1592 DLBCL, 1075 CLL/SLL, 336 marginal zone lymphoma (MZL),
262 mantle cell lymphoma, 306 T-cell lymphoma and 878 rare or unspecified NHL cases
and 5220 controls from the SCALE2, SF2, BC, Mayo, NCI-SEER, Yale and NSW studies
(<xref ref-type="table" rid="pgen-1001378-t001">Table 1</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s007">Table S1</xref>, <xref ref-type="fig" rid="pgen-1001378-g001">Figure 1</xref>). Among these SNPs,
rs10484561 showed evidence of association with DLBCL
(OR = 1.36,
P = 1.41×10<sup>−7</sup>) (<xref ref-type="supplementary-material" rid="pgen.1001378.s001">Figure S1B</xref>) and
all NHL (OR = 1.23,
P = 6.81×10<sup>−7</sup>). ORs were consistent
across the seven studies. There was also a suggestive association for rs2647012 with
MZL (OR = 1.32,
P = 6.34×10<sup>−4</sup>) (<xref ref-type="table" rid="pgen-1001378-t003">Table.3</xref>), consistent across six
studies.</p><p>Finally, we investigated the possibility of additional susceptibility loci for FL
outside of the HLA region by performing a joint analysis of the top 41 to 1000
variants of our scan and the previously published GWAS of follicular lymphoma <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>. From this
combined analysis, we did not find any additional markers with a strong association
(P<10<sup>−6</sup>) with FL that were not in LD with our top 5 markers
taken forward to stage 3 (data not shown).</p><table-wrap id="pgen-1001378-t003" position="float"><object-id pub-id-type="doi">10.1371/journal.pgen.1001378.t003</object-id><label>Table 3</label><caption><title>Meta-analysis of associations between rs1048456, the top 5 markers, and
non-Hodgkin lymphoma (NHL) subtypes (including follicular lymphoma
[FL], diffuse large B-cell lymphoma [DLBCL], chronic
lymphocytic leukemia/small lymphocytic lymphoma [CLL/SLL], and
others) and overall (All NHL).</title></caption><alternatives><graphic id="pgen-1001378-t003-3" xlink:href="pgen.1001378.t003"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col><col align="center" span="1"></col></colgroup><thead><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">FL<xref ref-type="table-fn" rid="nt107">*</xref></td><td align="left" rowspan="1" colspan="1">DLBCL</td><td align="left" rowspan="1" colspan="1">CLL/SLL</td><td align="left" rowspan="1" colspan="1">Marginal zone</td><td align="left" rowspan="1" colspan="1">Mantle cell</td><td align="left" rowspan="1" colspan="1">T-cell</td><td align="left" rowspan="1" colspan="1">All NHL<xref ref-type="table-fn" rid="nt107">*</xref></td></tr><tr><td align="left" rowspan="1" colspan="1">Marker</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td><td align="left" rowspan="1" colspan="1"><italic>P</italic>-value</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" rowspan="1" colspan="1">OR (95% CI)</td></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>rs10484561</bold></td><td align="left" rowspan="1" colspan="1">1.06×10<sup>−21</sup></td><td align="left" rowspan="1" colspan="1">1.41×10<sup>−7</sup></td><td align="left" rowspan="1" colspan="1">0.05</td><td align="left" rowspan="1" colspan="1">0.31</td><td align="left" rowspan="1" colspan="1">0.54</td><td align="left" rowspan="1" colspan="1">0.22</td><td align="left" rowspan="1" colspan="1">6.81×10<sup>−7</sup></td></tr><tr><td align="left" rowspan="1" colspan="1">chr6:32773398 <italic>HLA-DQB1</italic></td><td align="left" rowspan="1" colspan="1">1.94 (1.70–2.21)</td><td align="left" rowspan="1" colspan="1">1.36 (1.21–1.52)</td><td align="left" rowspan="1" colspan="1">0.85 (0.73–1.00)</td><td align="left" rowspan="1" colspan="1">0.87 (0.66–1.14)</td><td align="left" rowspan="1" colspan="1">0.91 (0.68–1.22)</td><td align="left" rowspan="1" colspan="1">0.84 (0.64–1.12)</td><td align="left" rowspan="1" colspan="1">1.23 (1.13–1.34)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>rs2647012</bold></td><td align="left" rowspan="1" colspan="1">6.53×10<sup>−16</sup></td><td align="left" rowspan="1" colspan="1">0.36</td><td align="left" rowspan="1" colspan="1">0.12</td><td align="left" rowspan="1" colspan="1">6.34×10<sup>−4</sup></td><td align="left" rowspan="1" colspan="1">0.15</td><td align="left" rowspan="1" colspan="1">0.04</td><td align="left" rowspan="1" colspan="1">0.02</td></tr><tr><td align="left" rowspan="1" colspan="1">chr6:32772436 <italic>HLA-DQB1</italic></td><td align="left" rowspan="1" colspan="1">0.65 (0.58–0.72)</td><td align="left" rowspan="1" colspan="1">0.96 (0.88–1.05)</td><td align="left" rowspan="1" colspan="1">0.92 (0.84–1.02)</td><td align="left" rowspan="1" colspan="1">1.32 (1.13–1.55)</td><td align="left" rowspan="1" colspan="1">1.14 (0.95–1.36)</td><td align="left" rowspan="1" colspan="1">1.20 (1.01–1.41)</td><td align="left" rowspan="1" colspan="1">0.94 (0.89–0.99)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>rs6536942</bold></td><td align="left" rowspan="1" colspan="1">0.06</td><td align="left" rowspan="1" colspan="1">0.22</td><td align="left" rowspan="1" colspan="1">0.53</td><td align="left" rowspan="1" colspan="1">0.28</td><td align="left" rowspan="1" colspan="1">0.51</td><td align="left" rowspan="1" colspan="1">0.56</td><td align="left" rowspan="1" colspan="1">0.07</td></tr><tr><td align="left" rowspan="1" colspan="1">chr4:167205644 <italic>TLL1</italic></td><td align="left" rowspan="1" colspan="1">1.18 (1.00–1.40)</td><td align="left" rowspan="1" colspan="1">1.09 (0.95–1.24)</td><td align="left" rowspan="1" colspan="1">1.05 (0.90–1.22)</td><td align="left" rowspan="1" colspan="1">1.14 (0.90–1.46)</td><td align="left" rowspan="1" colspan="1">0.91 (0.68–1.22)</td><td align="left" rowspan="1" colspan="1">1.08 (0.84–1.40)</td><td align="left" rowspan="1" colspan="1">1.08 (0.99–1.18)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>rs9277554</bold></td><td align="left" rowspan="1" colspan="1">0.08</td><td align="left" rowspan="1" colspan="1">0.42</td><td align="left" rowspan="1" colspan="1">0.20</td><td align="left" rowspan="1" colspan="1">0.99</td><td align="left" rowspan="1" colspan="1">0.08</td><td align="left" rowspan="1" colspan="1">0.18</td><td align="left" rowspan="1" colspan="1">0.93</td></tr><tr><td align="left" rowspan="1" colspan="1">chr6:33163516 <italic>HLA-DPB1</italic></td><td align="left" rowspan="1" colspan="1">0.91 (0.81–1.01)</td><td align="left" rowspan="1" colspan="1">0.96 (0.87–1.06)</td><td align="left" rowspan="1" colspan="1">1.07 (0.96–1.19)</td><td align="left" rowspan="1" colspan="1">1.00 (0.84–1.19)</td><td align="left" rowspan="1" colspan="1">1.19 (0.98–1.44)</td><td align="left" rowspan="1" colspan="1">1.13 (0.94–1.36)</td><td align="left" rowspan="1" colspan="1">1.00 (0.94–1.06)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>rs441890</bold></td><td align="left" rowspan="1" colspan="1">0.91</td><td align="left" rowspan="1" colspan="1">0.14</td><td align="left" rowspan="1" colspan="1">0.74</td><td align="left" rowspan="1" colspan="1">0.47</td><td align="left" rowspan="1" colspan="1">0.63</td><td align="left" rowspan="1" colspan="1">0.95</td><td align="left" rowspan="1" colspan="1">0.37</td></tr><tr><td align="left" rowspan="1" colspan="1">chr8:71727221 <italic>LACTB2</italic></td><td align="left" rowspan="1" colspan="1">1.01 (0.90–1.13)</td><td align="left" rowspan="1" colspan="1">1.07 (0.98–1.17)</td><td align="left" rowspan="1" colspan="1">1.02 (0.92–1.12)</td><td align="left" rowspan="1" colspan="1">1.06 (0.90–1.25)</td><td align="left" rowspan="1" colspan="1">0.96 (0.80–1.15)</td><td align="left" rowspan="1" colspan="1">0.99 (0.84–1.18)</td><td align="left" rowspan="1" colspan="1">1.03 (0.97–1.09)</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>rs716183</bold></td><td align="left" rowspan="1" colspan="1">0.84</td><td align="left" rowspan="1" colspan="1">0.78</td><td align="left" rowspan="1" colspan="1">0.35</td><td align="left" rowspan="1" colspan="1">0.59</td><td align="left" rowspan="1" colspan="1">0.94</td><td align="left" rowspan="1" colspan="1">0.80</td><td align="left" rowspan="1" colspan="1">0.49</td></tr><tr><td align="left" rowspan="1" colspan="1">chr10:118894485<italic>VAX1</italic></td><td align="left" rowspan="1" colspan="1">0.99 (0.88–1.10)</td><td align="left" rowspan="1" colspan="1">0.99 (0.90–1.08)</td><td align="left" rowspan="1" colspan="1">0.95 (0.87–1.05)</td><td align="left" rowspan="1" colspan="1">1.05 (0.89–1.23)</td><td align="left" rowspan="1" colspan="1">1.01 (0.84–1.20)</td><td align="left" rowspan="1" colspan="1">0.98 (0.83–1.16)</td><td align="left" rowspan="1" colspan="1">0.98 (0.93–1.04)</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="nt107"><label></label><p>*Excluding SCALE1 for FL.</p></fn><fn id="nt108"><label></label><p>OR: odds ratio, CI: confidence interval.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3"><title>Discussion</title><p>Through the identification of a second variant, rs2647012, that is independent of the
previously identified risk variant rs10484561 <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref> within the 6p21.32 region, our
findings substantiate a major link between HLA class II loci and genetic
susceptibility to FL. In addition, our study revealed evidence that rs10484561 is
associated with DLBCL risk suggesting some shared biological mechanisms of
susceptibility between these two common NHL subtypes. The association of rs2647012
with FL risk was not detected in earlier GWAS studies <xref rid="pgen.1001378-Skibola1" ref-type="bibr">[5]</xref>, <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>, and that of rs10484561 with
DLBCL risk previously reported was only marginal <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>, perhaps because of the smaller
sample sizes in Stage 1. The number of FL cases scanned in this study was almost
double compared to the previous individual GWAS <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>.</p><p>HLA class II molecules are expressed in antigen presenting cells such as
B-lymphocytes, and act to present exogenous antigens to CD4+ helper T-cells.
Efficiency of antigen presentation may influence lymphomagenesis through effects on
anti-tumor immunity or on immune response to infections that are directly or
indirectly oncogenic (e.g., through viral genome insertion or nonspecific chronic
antigenic stimulation) <xref rid="pgen.1001378-Bateman1" ref-type="bibr">[19]</xref>. Allelic variants in coding regions may affect the
structure of the peptide binding groove of the class II molecules, leading to
differences in the efficiency of oncogenic peptide binding or T-cell recognition.
Coding sequence variation in the molecules encoded by the extended
<italic>HLA-DRB1*0101-HLA-DQA1*0101-HLA-DQB1*0501</italic> haplotype
may be responsible for the association at rs10484561 <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>.</p><p>Alternatively, variants in the regulatory sequences may influence the expression
level of the HLA molecules and consequently the efficiency of antigen presentation.
We note that rs2647012 is strongly associated with the average expression levels of
<italic>HLA-DRB4</italic> (β = 0.78,
P = 3.4×10<sup>-22</sup>) and
<italic>HLA-DQA1</italic> (β = -0.58,
P = 5.1×10<sup>−13</sup>) probes in
Epstein-Barr virus-transfected lymphoblastoid cell lines (mRNA by SNP browser) <xref rid="pgen.1001378-Dixon1" ref-type="bibr">[20]</xref>, and rs10484561
is also associated with the expression levels of <italic>HLA-DQA1</italic> probes
(β = -0.884,
P = 1.6×10<sup>−10</sup>). We speculate that
this may be an alternative mechanism underlying the observed associations,
especially at rs2647012.</p><p>Interestingly, SNPs within the same LD block harboring rs2647012
(r<sup>2</sup>>0.7 in HapMap CEU) have previously been associated with rheumatoid
arthritis with the same direction of effect <xref rid="pgen.1001378-Plenge1" ref-type="bibr">[21]</xref>. Since autoimmune disorders
such as rheumatoid arthritis and Sjögren syndrome are associated with increased
risk of NHL, in particular with DLBCL but also with FL <xref rid="pgen.1001378-Baecklund1" ref-type="bibr">[22]</xref>, our finding may suggest a
molecular link between these diseases, although their associations within this
region of high LD could also be due to different causal variants.</p><p>Previously, large-scale candidate gene studies have pointed to susceptibility loci in
the HLA class III region mainly between the <italic>TNF</italic> variant
<italic>–</italic>308G->A (rs1800629) and risk of DLBCL <xref rid="pgen.1001378-Rothman1" ref-type="bibr">[23]</xref>, <xref rid="pgen.1001378-Skibola2" ref-type="bibr">[24]</xref>. We provide
novel evidence of association of DLBCL with an independent HLA marker in the class
II region (rs10484561; r<sup>2</sup> = 0), 1.1Mb away from
rs1800629, strongly suggesting that alleles in the HLA class II region may play an
important role in the pathogenesis of this subtype as well. The weaker association
of rs10484561 with DLBCL (OR 1.36) than with FL (OR 1.95) <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref> could imply that the
DLBCL-association is confined to a subset of DLBCL tumors with specific
morphological or molecular features more closely related to FL, such as the germinal
center-like B-cell phenotype <xref rid="pgen.1001378-Alizadeh1" ref-type="bibr">[25]</xref>. However, the observed effects could also be due to
modification of other concurrent DLBCL-specific susceptibility variants, or
rs10484561 could tag a more strongly associated marker in this region of high
LD.</p><p>Moreover, we found suggestive evidence of association at rs6536942 on 4q32.3, located
within an intron of the tolloid-like 1 (<italic>TLL1</italic>) gene, with FL risk.
However, larger studies are needed to validate this finding. Although the strongest
associations so far have been observed in the HLA region, and extended pooling of
available scan data failed to identify additional loci outside of HLA, we expect
that future larger meta-GWAS efforts will more robustly identify additional loci in
other regions.</p><p>In conclusion, our results strongly suggest that future genetic and functional work
focused on the HLA class II region will provide important insight into the disease
pathology of FL, DLBCL and other subtypes of NHL. In addition, further studies of
this region and potential interaction with environmental factors in NHL risk, and of
NHL prognosis are warranted.</p></sec><sec sec-type="methods" id="s4"><title>Methods</title><sec id="s4a"><title>Ethics statement</title><p>The studies described in this manuscript have been approved by the ethics
committee of the respective institutions: Karolinska Institutet (Sweden),
Scientific Ethics Committee system (Denmark), University of California, Berkeley
(US), National Cancer Institute, National Institutes of Health (US), Mayo Clinic
(US), University of British Columbia (Canada), Yale University (US), University
of Sydney (Australia).</p></sec><sec id="s4b"><title>Study subjects</title><p>The SCALE study is a population-based study of the etiology of NHL carried out in
all of Denmark and Sweden during 1999 to 2002 <xref rid="pgen.1001378-Smedby1" ref-type="bibr">[26]</xref>. NHL subtype diagnoses were
reviewed and reclassified according to the World Health Organization (WHO)
classification <xref rid="pgen.1001378-Jaffe1" ref-type="bibr">[1]</xref> as previously described <xref rid="pgen.1001378-Smedby1" ref-type="bibr">[26]</xref>. For this GWAS (SCALE1) we
used DNA from 400 cases with follicular lymphoma (FL; 150 from Denmark and 250
from Sweden) and from 150 Danish controls, individually matched to the Danish FL
cases by sex and age at study inclusion. We also used material collected from
673 control subjects in a separate Swedish population-based case-control study
of rheumatoid arthritis (the Eira study) <xref rid="pgen.1001378-Plenge1" ref-type="bibr">[21]</xref>, <xref rid="pgen.1001378-Plenge2" ref-type="bibr">[27]</xref>. The latter was conducted
during 1996 to 2005 among residents 18 to 70 years of age in the southern and
central parts of Sweden (including 90% of Swedish residents). Hence, the
population controls recruited in this study were considered to represent the
same study population as the Swedish component of the SCALE study with regard to
genetic variation. Genotyping completion rates were similar between cases and
controls; out of 400 cases and 823 controls genotyped, 379 cases (95%)
and 791 controls (96%) were included in the final analysis. Study
subjects used in Stages 2, 3 and validation in other NHL subtypes (<xref ref-type="table" rid="pgen-1001378-t001">Table 1</xref>, <xref ref-type="supplementary-material" rid="pgen.1001378.s007">Table S1</xref>,
<xref ref-type="supplementary-material" rid="pgen.1001378.s008">S2</xref>)
have been previously described <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>, <xref rid="pgen.1001378-Cerhan1" ref-type="bibr">[8]</xref>–<xref rid="pgen.1001378-Spinelli1" ref-type="bibr">[12]</xref>, and details are
available as supporting text (<xref ref-type="supplementary-material" rid="pgen.1001378.s018">Text S1</xref>). For the SCALE2 NHL subtype
validation study, we used the rest of the lymphoma cases with blood samples
originally recruited in SCALE (n = 1869), Danish control
subjects not included in the GWAS (n = 556), a second set
of control subjects from the Eira study (n = 742) and a
third group of controls recruited in a national population-based case-control
study of breast cancer, the Cancer and Hormones Replacement in Sweden (CAHRES)
study <xref rid="pgen.1001378-Magnusson1" ref-type="bibr">[28]</xref>(n = 720). The control subjects from this study were
randomly selected from the Swedish general population to match the expected age
distribution of the participating breast cancer cases (50 to 74 years).</p></sec><sec id="s4c"><title>Genotyping</title><p>Stage I genotyping of 317,503 single nucleotide polymorphisms (SNPs) was done on
the HumanHap300 (version 1.0) array. Validation genotyping was done using
Sequenom iPlex; SNPs in the human leukocyte antigen (HLA) region that failed
primer design for Sequenom assays were genotyped using Taqman (Applied
Biosystems).</p></sec><sec id="s4d"><title>Genome-wide association study</title><p>The scan included 317,503 SNPs from the HumanHap300 (version 1.0) array. The
datasets were filtered on the basis of SNP genotyping call rates
(≥>95% completeness), sample completion rate (≥90%),
minor allele frequency (MAF; all subjects as well as cases and controls
separately ≥0.03) and non-deviation from Hardy-Weinberg equilibrium (HWE;
p<10<sup>−6</sup>). We also excluded SNPs with cluster plot
problems, and those on the X and Y chromosomes. Study subjects with gender
discrepancies and/or labelling errors were removed. We also removed individual
samples with evidence of cryptic family relationships (identified using
the–genome command in PLINK). To detect outliers in terms of population
stratification, we performed principal component (PC) analysis using the
EIGENSTRAT software (<xref ref-type="supplementary-material" rid="pgen.1001378.s004">Figure S4</xref>). A subset of linkage
disequilibrium (LD) thinned SNPs was selected such that all pair-wise
associations had r<sup>2</sup><0.2, and long-range regions of high LD,
reported to potentially confound genome scans, were removed <xref rid="pgen.1001378-Price1" ref-type="bibr">[29]</xref>. Twenty-five
samples were removed as population outliers on the basis of their values on the
first three PCs. To adjust for possible stratification in our association
analyses we adjusted the regression analyses using the first three PCs; the
number of PCs used for adjustment was determined by plotting the eigenvalues and
locating the position of the “elbow” on the scree plot (<xref ref-type="supplementary-material" rid="pgen.1001378.s005">Figure S5</xref>).
Wald tests, treating minor allele counts as continuous covariates were used to
test for association. The genomic inflation factor (λ) was calculated to be
1.0283 after adjusting for the first three PCs, suggesting the presence of
minimal stratification. Quantile-quantile plots for the associations before and
after adjustment are shown in <xref ref-type="supplementary-material" rid="pgen.1001378.s006">Figure S6</xref>. Finally, we assessed associations
of age and sex with main genotypes among the control subjects to address the
possibility of confounding by these factors (<xref ref-type="supplementary-material" rid="pgen.1001378.s017">Table S11</xref>).
As there was no evidence of associations of age or sex with genotypes among the
controls, we did not adjust for them in the final main effects analyses of
genotypes.</p></sec><sec id="s4e"><title>Validation and meta-analysis</title><p>In Stage 2, similar quality control measures were applied as in Stage 1,
including genotyping call rate ≥95%, sample completion rate
≥90%, and MAF ≥0.05. We tested each validation study for
association using trend tests. For meta-analyses across studies and NHL
subtypes, we used the Cochran-Mantel-Haenszel method to calculate the combined
odds ratio and P-value, and χ<sup>2</sup> tests for heterogeneity.
Multivariate logistic regression was used to test for independence of SNP
effects. For validation among other NHL subtypes, the control subjects were the
same as those in Stages 2 and 3 for validation in FL for all studies except
SCALE2. Only European-ancestry subjects were included, and the possibility of
population stratification affecting the results has been thoroughly explored and
found to be low in earlier investigations in the same populations <xref rid="pgen.1001378-Conde1" ref-type="bibr">[6]</xref>, <xref rid="pgen.1001378-Cerhan1" ref-type="bibr">[8]</xref>.</p></sec><sec id="s4f"><title>Imputation</title><p>We used IMPUTEv1 for the imputation of SNPs from the 1000 Genomes pilot1 CEU data
(August 2009 release); and the HapMap Phase II release 22 CEU data. We set a
strict threshold for imputation, using only SNPs with confidence scores of
≥0.9, call rates ≥90%, non-deviation from Hardy-Weinberg
equilibrium P >0.001 and MAF >0.01. The imputation was done on the Stage 1
samples separately for each of the two reference datasets and SNPs showing a
discordance of >5% between the genotypes imputed with the two datasets
were excluded from further analysis. The data were then merged using HapMap II
as the master dataset to which additional imputed SNPs from the 1000 Genomes
dataset were added. HLA alleles were imputed by identifying tag SNPs <xref rid="pgen.1001378-deBakker2" ref-type="bibr">[15]</xref> from the
genotyped and imputed SNP dataset. We used PLINK for haplotype imputation with
the tag SNPs and downstream association analyses. Only haplotypes with call
rates >90%, MAF>1% and probability thresholds >0.8 were
analyzed.</p></sec><sec id="s4g"><title>Haplotype and coalescence analyses</title><p>For coalescence analysis all 12 SNPs (genotyped in this study and within a region
of ∼177 Kb) adjacent to the two SNPs associated with the FL risk were used
to construct haplotypes. These were phased using the PHASE program <xref rid="pgen.1001378-Stephens1" ref-type="bibr">[30]</xref> and
tested for association using PLINK. The ancestral haplotype was constructed from
the chimpanzee (PanTro2) allele whenever possible, and otherwise from the
macaque alleles. An ancestral recombination graph was constructed using the
program Beagle <xref rid="pgen.1001378-Song1" ref-type="bibr">[13]</xref>, <xref rid="pgen.1001378-Lyngs1" ref-type="bibr">[31]</xref> which allows recombination assuming an infinite site
mutation model. After identifying the first recombination event the haplotype
segment before the recombination spot was used to construct a median
–joining network using the Network program <xref rid="pgen.1001378-Bandelt1" ref-type="bibr">[14]</xref>. The alleles of the
imputed SNP rs9378212 were then phased on each haplotype segment using the PHASE
program.</p><p>The URLs for the data and analytic approaches presented herein are as
follows:</p><p>1000 Genomes <ext-link ext-link-type="uri" xlink:href="http://1000genomes.org">http://1000genomes.org</ext-link></p><p>HapMapII <ext-link ext-link-type="uri" xlink:href="http://www.hapmap.org">http://www.hapmap.org</ext-link></p><p>IMPUTEv1 <ext-link ext-link-type="uri" xlink:href="https://mathgen.stats.ox.ac.uk/impute/impute_v1.html">https://mathgen.stats.ox.ac.uk/impute/impute_v1.html</ext-link></p><p>mRNA by SNP browser <ext-link ext-link-type="uri" xlink:href="http://www.sph.umich.edu/csg/liang/asthma/">http://www.sph.umich.edu/csg/liang/asthma/</ext-link></p><p>R script for recombination plot <ext-link ext-link-type="uri" xlink:href="http://www.broadinstitute.org/science/projects/diabetes-genetics-initiative/plotting-genome-wide-association-results">http://www.broadinstitute.org/science/projects/diabetes-genetics-initiative/plotting-genome-wide-association-results</ext-link></p></sec></sec><sec sec-type="supplementary-material" id="s5"><title>Supporting Information</title><supplementary-material content-type="local-data" id="pgen.1001378.s001"><label>Figure S1</label><caption><p>Forest plots of main associations with risk of follicular lymphoma (FL) and
diffuse large B-cell lymphoma (DLBCL).</p><p>(0.18 MB PDF)</p></caption><media xlink:href="pgen.1001378.s001.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s002"><label>Figure S2</label><caption><p>Association results for imputed SNPs and genotyped SNPs.</p><p>(0.03 MB PDF)</p></caption><media xlink:href="pgen.1001378.s002.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s003"><label>Figure S3</label><caption><p>Ancestral reconstruction graph based on the 14 SNPs in the Stage 1
samples.</p><p>(0.05 MB PDF)</p></caption><media xlink:href="pgen.1001378.s003.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s004"><label>Figure S4</label><caption><p>Testing of population structure using principal components analysis.</p><p>(0.11 MB PDF)</p></caption><media xlink:href="pgen.1001378.s004.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s005"><label>Figure S5</label><caption><p>Principal components analysis scree plot.</p><p>(0.02 MB PDF)</p></caption><media xlink:href="pgen.1001378.s005.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s006"><label>Figure S6</label><caption><p>Quantile-quantile plots before and after genomic control correction.</p><p>(0.07 MB PDF)</p></caption><media xlink:href="pgen.1001378.s006.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s007"><label>Table S1</label><caption><p>Number of patients with Non-Hodgkin lymphoma subtypes other than follicular
lymphoma.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s007.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s008"><label>Table S2</label><caption><p>Overlap of samples from the current genome-wide association study and the
previous GWAS reporting association between 6p21.32 and follicular lymphoma
risk.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s008.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s009"><label>Table S3</label><caption><p>Top 40 SNPs taken forward to Stage 2, sorted by significance level (trend
P-value) of association with risk of follicular lymphoma.</p><p>(0.02 MB PDF)</p></caption><media xlink:href="pgen.1001378.s009.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s010"><label>Table S4</label><caption><p>SNPs on chromosome 6p21.32 that showed genome-wide per allele P-values <
1E-04 in association with risk of follicular lymphoma in Stage 1, sorted by
position.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s010.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s011"><label>Table S5</label><caption><p>Summary statistics for associations with risk of follicular lymphoma in
Stages 1 and 2 with combined P-values.</p><p>(0.02 MB PDF)</p></caption><media xlink:href="pgen.1001378.s011.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s012"><label>Table S6</label><caption><p>Crude and adjusted logistic regression analyses of the six SNPs in 6p21.32
showing significant association with risk of follicular lymphoma in Stages 1
and 2.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s012.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s013"><label>Table S7</label><caption><p>Individual study results for associations between the 5 SNPs taken forward to
Stage 3 and risk of follicular lymphoma in Stage 3.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s013.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s014"><label>Table S8</label><caption><p>Genotype counts of main SNPs per Cases/Controls, per study and in total.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s014.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s015"><label>Table S9</label><caption><p>Associations with risk of follicular lymphoma for haplotypes phased with 14
SNPs or 7 SNPs based on genotyped SNPs in Stage 1.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s015.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s016"><label>Table S10</label><caption><p>Imputation of HLA class II alleles and risk of follicular lymphoma.</p><p>(0.01 MB PDF)</p></caption><media xlink:href="pgen.1001378.s016.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s017"><label>Table S11</label><caption><p>Trend p-value of associations of age and sex with main genotypes among
controls subjects per study.</p><p>(0.02 MB PDF)</p></caption><media xlink:href="pgen.1001378.s017.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pgen.1001378.s018"><label>Text S1</label><caption><p>Additional description of validation study subjects.</p><p>(0.04 MB PDF)</p></caption><media xlink:href="pgen.1001378.s018.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material></sec></body><back><ack><p>We are grateful to X. Y. Chen, H. B. Toh, K. K. Heng, W. Y. Meah, C. H. Wong, and H.
Q. Low from the Genome Institute of Singapore for their support in genotyping
analyses and data processing for the SCALE study. The control samples from the
CAHRES study were provided by Per Hall and Kamila Czene.</p></ack><fn-group><fn fn-type="COI-statement"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type="financial-disclosure"><p>This work was funded by the Agency for Science and Technology and Research of
Singapore (A*STAR), the Swedish Cancer Society (090659), the Swedish
Research Council (K2008-64X-20737-01-2, 523-2006-972), and the Danish Medical
Research Council (FSS 09-63424). The collection of blood samples in the founding
case-control study was supported by the National Cancer Institute (NCI)
(CA069269-01). Sample collection in EIRA was supported by the Swedish Council
for Working life (2008-0567), the AFA insurance company, and by the Combine
project founded by Vinnova. The SF1 and SF2 studies were supported by the NCI,
National Institutes of Health (NIH) (CA122663, CA104682, CA45614, CA89745). The
NCI-SEER study was supported by the Intramural Research Program of the NIH (NCI)
and by Public Health Service contracts N01-PC-65064, N01-PC-67008, N01-PC-67009,
N01-PC-67010, and N02-PC-71105. The Mayo study was supported by the NIH (NCI)
(R01- CA91253, R01-CA118444). The NSW study was supported by a National Health
and Medical Research Council of Australia project grant, Cancer Council NSW, a
University of Sydney Medical Foundation Program Grant, and the Intramural
Research Program of the US NIH (NCI). The Yale study was supported by grant
CA62006 from NIH (NCI) and the Intramural Research Program of the National
Institutes of Health (NCI). The BC study was funded from the Canadian Cancer
Society and the Canadian Institutes of Health Research. ARB-W is a Senior
Scholar of the Michael Smith Foundation for Health Research. The funders had no
role in study design, data collection and analysis, decision to publish, or
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