A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer
Abstract Background Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods We complemented a new conventional...
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-02-01
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| Series: | Genome Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13073-020-00816-4 |
| _version_ | 1818459730766462976 |
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| author | Evangelina López de Maturana Juan Antonio Rodríguez Lola Alonso Oscar Lao Esther Molina-Montes Isabel Adoración Martín-Antoniano Paulina Gómez-Rubio Rita Lawlor Alfredo Carrato Manuel Hidalgo Mar Iglesias Xavier Molero Matthias Löhr Christopher Michalski José Perea Michael O’Rorke Victor Manuel Barberà Adonina Tardón Antoni Farré Luís Muñoz-Bellvís Tanja Crnogorac-Jurcevic Enrique Domínguez-Muñoz Thomas Gress William Greenhalf Linda Sharp Luís Arnes Lluís Cecchini Joaquim Balsells Eithne Costello Lucas Ilzarbe Jörg Kleeff Bo Kong Mirari Márquez Josefina Mora Damian O’Driscoll Aldo Scarpa Weimin Ye Jingru Yu PanGenEU Investigators Montserrat García-Closas Manolis Kogevinas Nathaniel Rothman Debra T Silverman SBC/EPICURO Investigators Demetrius Albanes Alan A Arslan Laura Beane-Freeman Paige M Bracci Paul Brennan Bas Bueno-de-Mesquita Julie Buring Federico Canzian Margaret Du Steve Gallinger J Michael Gaziano Phyllis J Goodman Marc Gunter Loic LeMarchand Donghui Li Rachael E Neale Ulrika Peters Gloria M Petersen Harvey A Risch Maria José Sánchez Xiao-Ou Shu Mark D Thornquist Kala Visvanathan Wei Zheng Stephen J Chanock Douglas Easton Brian M Wolpin Rachael Z Stolzenberg-Solomon Alison P Klein Laufey T Amundadottir Marc A Marti-Renom Francisco X Real Núria Malats |
| author_facet | Evangelina López de Maturana Juan Antonio Rodríguez Lola Alonso Oscar Lao Esther Molina-Montes Isabel Adoración Martín-Antoniano Paulina Gómez-Rubio Rita Lawlor Alfredo Carrato Manuel Hidalgo Mar Iglesias Xavier Molero Matthias Löhr Christopher Michalski José Perea Michael O’Rorke Victor Manuel Barberà Adonina Tardón Antoni Farré Luís Muñoz-Bellvís Tanja Crnogorac-Jurcevic Enrique Domínguez-Muñoz Thomas Gress William Greenhalf Linda Sharp Luís Arnes Lluís Cecchini Joaquim Balsells Eithne Costello Lucas Ilzarbe Jörg Kleeff Bo Kong Mirari Márquez Josefina Mora Damian O’Driscoll Aldo Scarpa Weimin Ye Jingru Yu PanGenEU Investigators Montserrat García-Closas Manolis Kogevinas Nathaniel Rothman Debra T Silverman SBC/EPICURO Investigators Demetrius Albanes Alan A Arslan Laura Beane-Freeman Paige M Bracci Paul Brennan Bas Bueno-de-Mesquita Julie Buring Federico Canzian Margaret Du Steve Gallinger J Michael Gaziano Phyllis J Goodman Marc Gunter Loic LeMarchand Donghui Li Rachael E Neale Ulrika Peters Gloria M Petersen Harvey A Risch Maria José Sánchez Xiao-Ou Shu Mark D Thornquist Kala Visvanathan Wei Zheng Stephen J Chanock Douglas Easton Brian M Wolpin Rachael Z Stolzenberg-Solomon Alison P Klein Laufey T Amundadottir Marc A Marti-Renom Francisco X Real Núria Malats |
| author_sort | Evangelina López de Maturana |
| collection | DOAJ |
| description | Abstract Background Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. Results We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8—a lncRNA associated with pancreatic carcinogenesis—with a lowest p value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1—a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support. Conclusions This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases. |
| first_indexed | 2024-12-14T23:19:00Z |
| format | Article |
| id | doaj.art-fd82873a71df49c79bdc3dadb14c043b |
| institution | Directory Open Access Journal |
| issn | 1756-994X |
| language | English |
| last_indexed | 2024-12-14T23:19:00Z |
| publishDate | 2021-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj.art-fd82873a71df49c79bdc3dadb14c043b2022-12-21T22:44:01ZengBMCGenome Medicine1756-994X2021-02-0113111810.1186/s13073-020-00816-4A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancerEvangelina López de Maturana0Juan Antonio Rodríguez1Lola Alonso2Oscar Lao3Esther Molina-Montes4Isabel Adoración Martín-Antoniano5Paulina Gómez-Rubio6Rita Lawlor7Alfredo Carrato8Manuel Hidalgo9Mar Iglesias10Xavier Molero11Matthias Löhr12Christopher Michalski13José Perea14Michael O’Rorke15Victor Manuel Barberà16Adonina Tardón17Antoni Farré18Luís Muñoz-Bellvís19Tanja Crnogorac-Jurcevic20Enrique Domínguez-Muñoz21Thomas Gress22William Greenhalf23Linda Sharp24Luís Arnes25Lluís Cecchini26Joaquim Balsells27Eithne Costello28Lucas Ilzarbe29Jörg Kleeff30Bo Kong31Mirari Márquez32Josefina Mora33Damian O’Driscoll34Aldo Scarpa35Weimin Ye36Jingru Yu37PanGenEU InvestigatorsMontserrat García-Closas38Manolis Kogevinas39Nathaniel Rothman40Debra T Silverman41SBC/EPICURO InvestigatorsDemetrius Albanes42Alan A Arslan43Laura Beane-Freeman44Paige M Bracci45Paul Brennan46Bas Bueno-de-Mesquita47Julie Buring48Federico Canzian49Margaret Du50Steve Gallinger51J Michael Gaziano52Phyllis J Goodman53Marc Gunter54Loic LeMarchand55Donghui Li56Rachael E Neale57Ulrika Peters58Gloria M Petersen59Harvey A Risch60Maria José Sánchez61Xiao-Ou Shu62Mark D Thornquist63Kala Visvanathan64Wei Zheng65Stephen J Chanock66Douglas Easton67Brian M Wolpin68Rachael Z Stolzenberg-Solomon69Alison P Klein70Laufey T Amundadottir71Marc A Marti-Renom72Francisco X Real73Núria Malats74Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST)Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST)Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)ARC-Net Centre for Applied Research on Cancer and Department of Pathology and Diagnostics, University and Hospital Trust of VeronaCIBERONCMadrid-Norte-Sanchinarro HospitalCIBERONCHospital Universitari Vall d’Hebron, Vall d’Hebron Research Institute (VHIR)Gastrocentrum, Karolinska Institutet and University HospitalDepartment of Surgery, Technical University of MunichDepartment of Surgery, Hospital 12 de Octubre, and Department of Surgery and Health Research Institute, Fundación Jiménez DíazCentre for Public Health, Queen’s University BelfastMolecular Genetics Laboratory, General University Hospital of ElcheDepartment of Medicine, Instituto Universitario de Oncología del Principado de Asturias (IUOPA), Instituto de Investigación Sanitaria del Principado de Asturias (ISPA)Department of Gastroenterology and Clinical Biochemistry, Hospital de la Santa Creu i Sant PauCIBERONCBarts Cancer Institute, Centre for Molecular Oncology, Queen Mary University of LondonDepartment of Gastroenterology, University Clinical Hospital of Santiago de CompostelaDepartment of Gastroenterology, University Hospital of Giessen and MarburgDepartment of Molecular and Clinical Cancer Medicine, University of LiverpoolNational Cancer Registry Ireland and HRB Clinical Research Facility, University College CorkCentre for Stem Cell Research and Developmental Biology, University of CopenhagenCIBERONCHospital Universitari Vall d’Hebron, Vall d’Hebron Research Institute (VHIR)Department of Molecular and Clinical Cancer Medicine, University of LiverpoolCIBERONCDepartment of Surgery, Technical University of MunichDepartment of Surgery, Technical University of MunichGenetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)Department of Gastroenterology and Clinical Biochemistry, Hospital de la Santa Creu i Sant PauNational Cancer Registry Ireland and HRB Clinical Research Facility, University College CorkARC-Net Centre for Applied Research on Cancer and Department of Pathology and Diagnostics, University and Hospital Trust of VeronaDepartment of Medical Epidemiology and Biostatistics, Karolinska InstitutetDepartment of Medical Epidemiology and Biostatistics, Karolinska InstitutetDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthCIBERESPDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthDepartment of Obstetrics and Gynecology, New York University School of MedicineDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthDepartment of Epidemiology and Biostatistics, University of CaliforniaInternational Agency for Research on Cancer (IARC)Deparment for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM)Division of Preventive Medicine, Brigham and Women’s HospitalGenomic Epidemiology Group, German Cancer Research Center (DKFZDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer CenterProsserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health SystemDepartments of Medicine, Brigham and Women’s Hospital, VA Boston and Harvard Medical SchoolSWOG Statistical Center, Fred Hutchinson Cancer Research CenterInternational Agency for Research on Cancer (IARC)Cancer Epidemiology Program, University of Hawaii Cancer CenterUniversity of Texas MD Anderson Cancer CenterPopulation Health Department, QIMR Berghofer Medical Research InstituteDivision of Public Health Sciences, Fred Hutchinson Cancer Research CenterDepartment of Health Sciences Research, Mayo Clinic College of MedicineDepartment of Chronic Disease Epidemiology, Yale School of Public HealthEscuela Andaluza de Salud Pública (EASP)Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of MedicineDivision of Public Health Sciences, Fred Hutchinson Cancer Research CenterDepartment of Health Sciences Research, Mayo Clinic College of MedicineDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of MedicineDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of CambridgeDepartment Medical Oncology, Dana-Farber Cancer InstituteDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthDepartment of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of MedicineLaboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of HealthNational Centre for Genomic Analysis (CNAG), Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Universitat Pompeu Fabra (UPF), ICREACIBERONCGenetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO)Abstract Background Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. Results We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8—a lncRNA associated with pancreatic carcinogenesis—with a lowest p value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1—a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support. Conclusions This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.https://doi.org/10.1186/s13073-020-00816-4Pancreatic cancer riskGenome-wide association analysisGenetic susceptibility3D genomic structureLocal indices of genome spatial autocorrelation |
| spellingShingle | Evangelina López de Maturana Juan Antonio Rodríguez Lola Alonso Oscar Lao Esther Molina-Montes Isabel Adoración Martín-Antoniano Paulina Gómez-Rubio Rita Lawlor Alfredo Carrato Manuel Hidalgo Mar Iglesias Xavier Molero Matthias Löhr Christopher Michalski José Perea Michael O’Rorke Victor Manuel Barberà Adonina Tardón Antoni Farré Luís Muñoz-Bellvís Tanja Crnogorac-Jurcevic Enrique Domínguez-Muñoz Thomas Gress William Greenhalf Linda Sharp Luís Arnes Lluís Cecchini Joaquim Balsells Eithne Costello Lucas Ilzarbe Jörg Kleeff Bo Kong Mirari Márquez Josefina Mora Damian O’Driscoll Aldo Scarpa Weimin Ye Jingru Yu PanGenEU Investigators Montserrat García-Closas Manolis Kogevinas Nathaniel Rothman Debra T Silverman SBC/EPICURO Investigators Demetrius Albanes Alan A Arslan Laura Beane-Freeman Paige M Bracci Paul Brennan Bas Bueno-de-Mesquita Julie Buring Federico Canzian Margaret Du Steve Gallinger J Michael Gaziano Phyllis J Goodman Marc Gunter Loic LeMarchand Donghui Li Rachael E Neale Ulrika Peters Gloria M Petersen Harvey A Risch Maria José Sánchez Xiao-Ou Shu Mark D Thornquist Kala Visvanathan Wei Zheng Stephen J Chanock Douglas Easton Brian M Wolpin Rachael Z Stolzenberg-Solomon Alison P Klein Laufey T Amundadottir Marc A Marti-Renom Francisco X Real Núria Malats A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer Genome Medicine Pancreatic cancer risk Genome-wide association analysis Genetic susceptibility 3D genomic structure Local indices of genome spatial autocorrelation |
| title | A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer |
| title_full | A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer |
| title_fullStr | A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer |
| title_full_unstemmed | A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer |
| title_short | A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer |
| title_sort | multilayered post gwas assessment on genetic susceptibility to pancreatic cancer |
| topic | Pancreatic cancer risk Genome-wide association analysis Genetic susceptibility 3D genomic structure Local indices of genome spatial autocorrelation |
| url | https://doi.org/10.1186/s13073-020-00816-4 |
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