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Stamp J, DenAdel A, Weinreich D, Crawford L. Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies. G3 (BETHESDA, MD.) 2023; 13:jkad118. [PMID: 37243672 PMCID: PMC10484060 DOI: 10.1093/g3journal/jkad118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 01/11/2023] [Accepted: 05/23/2023] [Indexed: 05/29/2023]
Abstract
Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this study, we present the "multivariate MArginal ePIstasis Test" (mvMAPIT)-a multioutcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact-thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search-based methods. Our proposed mvMAPIT builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate mvMAPIT as a multivariate linear mixed model and develop a multitrait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. With simulations, we illustrate the benefits of mvMAPIT over univariate (or single-trait) epistatic mapping strategies. We also apply mvMAPIT framework to protein sequence data from two broadly neutralizing anti-influenza antibodies and approximately 2,000 heterogeneous stock of mice from the Wellcome Trust Centre for Human Genetics. The mvMAPIT R package can be downloaded at https://github.com/lcrawlab/mvMAPIT.
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Affiliation(s)
- Julian Stamp
- Center for Computational Molecular Biology, Brown University, Providence, RI 02906, USA
| | - Alan DenAdel
- Center for Computational Molecular Biology, Brown University, Providence, RI 02906, USA
| | - Daniel Weinreich
- Center for Computational Molecular Biology, Brown University, Providence, RI 02906, USA
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02906, USA
| | - Lorin Crawford
- Center for Computational Molecular Biology, Brown University, Providence, RI 02906, USA
- Department of Biostatistics, Brown University, Providence, RI 02903, USA
- Microsoft Research New England, Cambridge, MA 02142, USA
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2
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Zhang R, Shen S, Wei Y, Zhu Y, Li Y, Chen J, Guan J, Pan Z, Wang Y, Zhu M, Xie J, Xiao X, Zhu D, Li Y, Albanes D, Landi MT, Caporaso NE, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Wichmann HE, Rennert G, Arnold S, Brennan P, McKay JD, Field JK, Shete SS, Le Marchand L, Liu G, Andrew AS, Kiemeney LA, Zienolddiny-Narui S, Behndig A, Johansson M, Cox A, Lazarus P, Schabath MB, Aldrich MC, Dai J, Ma H, Zhao Y, Hu Z, Hung RJ, Amos CI, Shen H, Chen F, Christiani DC. A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians. J Thorac Oncol 2022; 17:974-990. [PMID: 35500836 PMCID: PMC9512697 DOI: 10.1016/j.jtho.2022.04.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/13/2022] [Accepted: 04/20/2022] [Indexed: 01/12/2023]
Abstract
INTRODUCTION Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC). METHODS Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers. RESULTS With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification. CONCLUSIONS Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.
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Affiliation(s)
- Ruyang Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Sipeng Shen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yongyue Wei
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Ying Zhu
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Jiajin Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Jinxing Guan
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Zoucheng Pan
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yuzhuo Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Meng Zhu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Junxing Xie
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Xiangjun Xiao
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Dakai Zhu
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Yafang Li
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stephen Lam
- Department of Medicine, British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
| | - Adonina Tardon
- Faculty of Medicine, University of Oviedo and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Department of Epidemiology, University of Washington School of Public Health, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Angela Risch
- Department of Biosciences and Cancer Cluster Salzburg, University of Salzburg, Salzburg, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg August University Göttingen, Göttingen, Germany
| | - H-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians University, Munich, Germany
| | - Gadi Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Carmel, Haifa, Israel
| | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky
| | - Paul Brennan
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - James D McKay
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - John K Field
- Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Sanjay S Shete
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Angeline S Andrew
- Department of Epidemiology, Department of Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Lambertus A Kiemeney
- Department for Health Evidence, Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Annelie Behndig
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | | | - Angela Cox
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, United Kingdom
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, Washington
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Melinda C Aldrich
- Department of Thoracic Surgery and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Juncheng Dai
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yang Zhao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Zhibin Hu
- China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Christopher I Amos
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Hongbing Shen
- China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Feng Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China.
| | - David C Christiani
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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Vaidyanathan V, Naidu V, Karunasinghe N, Jabed A, Pallati R, Marlow G, R. Ferguson L. SNP-SNP interactions as risk factors for aggressive prostate cancer. F1000Res 2017; 6:621. [PMID: 28580135 PMCID: PMC5437948 DOI: 10.12688/f1000research.11027.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2017] [Indexed: 12/23/2022] Open
Abstract
Prostate cancer (PCa) is one of the most significant male health concerns worldwide. Single nucleotide polymorphisms (SNPs) are becoming increasingly strong candidate biomarkers for identifying susceptibility to PCa. We identified a number of SNPs reported in genome-wide association analyses (GWAS) as risk factors for aggressive PCa in various European populations, and then defined SNP-SNP interactions, using PLINK software, with nucleic acid samples from a New Zealand cohort. We used this approach to find a gene x environment marker for aggressive PCa, as although statistically gene x environment interactions can be adjusted for, it is highly impossible in practicality, and thus must be incorporated in the search for a reliable biomarker for PCa. We found two intronic SNPs statistically significantly interacting with each other as a risk for aggressive prostate cancer on being compared to healthy controls in a New Zealand population.
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Affiliation(s)
- Venkatesh Vaidyanathan
- Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand
- Auckland Cancer Society Research Centre, Auckland, New Zealand
| | - Vijay Naidu
- School of Engineering,Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
| | | | - Anower Jabed
- Department of Molecular Medicine and Pathology, FM & HS, University of Auckland, Auckland, New Zealand
| | - Radha Pallati
- Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand
| | - Gareth Marlow
- Experimental Cancer Medicine Centre, Cardiff University, Cardiff, UK
| | - Lynnette R. Ferguson
- Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand
- Auckland Cancer Society Research Centre, Auckland, New Zealand
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Shen J, Li Z, Song Z, Chen J, Shi Y. Genome-wide two-locus interaction analysis identifies multiple epistatic SNP pairs that confer risk of prostate cancer: A cross-population study. Int J Cancer 2017; 140:2075-2084. [PMID: 28124475 DOI: 10.1002/ijc.30622] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 01/11/2017] [Accepted: 01/12/2017] [Indexed: 01/05/2023]
Abstract
Prostate cancer is one of the most common carcinomas among adult males. Recently, genome-wide association studies (GWAS) have identified several susceptibility genes of prostate cancer. However, these single locus results can only explain a small proportion of the genetic etiology. In order to understand how multiple genetic variants may contribute to the penetrance of prostate cancer, we conducted a genome-wide SNP-SNP interaction study in four populations, involving 5,269 cases and 5,289 controls. We exhaustively evaluated all pairs of SNP-SNP interactions for 661,658 SNPs that were consensus in all four groups, and then performed a meta-analysis to combine the results. We found multiple variants within region 7p21.3 and 18p11.22 significantly interacted with each other and reached genome-wide significance levels. The most significant epistasis was between rs1105255 (intergenic, near RBSG3) and rs651431 (intergenic, near VAPA) (p = 1.4 × 10-14 ). Notably, VAPA was identified to be the protein-coding transcripts as PTEN competing endogenous RNA in prostate cancer. And PTEN is a critical tumor suppressor gene frequently altered in cancers. In addition, 7p21.3 involves several pseudogenes, whose parental genes are cancer-related. Recently, growing evidence strongly suggests they are of multifaceted involvements in the pathogenesis of cancer. Multiple regulatory elements were found within 7p21.3 and 18p11.22, indicating the variants might regulate the nearby genes and confer risk of disease. Additionally, we also found several other significant epistasis, most of which were near or in cancer-related genes. Drug target enrichment analysis suggested genes in top epistasis significantly overlapped with target genes of FDA-approved drugs for treatment of prostate cancer.
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Affiliation(s)
- Jiawei Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China.,Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China.,The Biomedical Sciences Institute of Qingdao University, Qingdao Branch of SJTU Bio-X Institutes, Qingdao, 266071, People's Republic of China
| | - Zhijian Song
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | - Jianhua Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, China.,The Biomedical Sciences Institute of Qingdao University, Qingdao Branch of SJTU Bio-X Institutes, Qingdao, 266071, People's Republic of China.,Department of Psychiatry, The First Teaching Hospital of Xinjiang Medical University, Urumqi, People's Republic of China
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5
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Liu M, Shi X, Yang F, Wang J, Xu Y, Wei D, Yang K, Zhang Y, Wang X, Liang S, Chen X, Sun L, Zhu X, Zhao C, Zhu L, Tang L, Zheng C, Yang Z. The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:162. [PMID: 26828504 PMCID: PMC4772182 DOI: 10.3390/ijerph13020162] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 01/15/2016] [Accepted: 01/18/2016] [Indexed: 01/15/2023]
Abstract
Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79–4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.
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Affiliation(s)
- Ming Liu
- Department of Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan 030001, China.
| | - Xiaohong Shi
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Fan Yang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
- Graduate School, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100005, China.
| | - Jianye Wang
- Department of Urology and Beijing Hospital, Chinese Ministry of Health, Beijing 100730, China.
| | - Yong Xu
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin 300211, China.
| | - Dong Wei
- Department of Urology and Beijing Hospital, Chinese Ministry of Health, Beijing 100730, China.
| | - Kuo Yang
- Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin 300211, China.
| | - Yaoguang Zhang
- Department of Urology and Beijing Hospital, Chinese Ministry of Health, Beijing 100730, China.
| | - Xin Wang
- Department of Urology and Beijing Hospital, Chinese Ministry of Health, Beijing 100730, China.
| | - Siying Liang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Xin Chen
- Department of Urology and Beijing Hospital, Chinese Ministry of Health, Beijing 100730, China.
| | - Liang Sun
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Xiaoquan Zhu
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Chengxiao Zhao
- Department of Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan 030001, China.
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Ling Zhu
- Medical Examination Centre, Beijing Hospital, Ministry of Health, Beijing 100730, China.
| | - Lei Tang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
| | - Chenguang Zheng
- Guangxi Zhuang Autonomous Region Women and Children Care Hospital, Nanning, Guangxi 530003, China.
| | - Ze Yang
- The Key Laboratory of Geriatrics, Beijing Hospital & Beijing Institute of Geriatrics, Ministry of Health, Beijing 100730, China.
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Li A, Meyre D. Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology. ACTA ACUST UNITED AC 2014; 10:101-117. [PMID: 25598767 PMCID: PMC4287874 DOI: 10.2174/1573400510666140319235334] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Revised: 02/07/2014] [Accepted: 04/18/2014] [Indexed: 12/12/2022]
Abstract
With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.
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Affiliation(s)
- Aihua Li
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON L8N 3Z5, Canada
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Milne RL, Herranz J, Michailidou K, Dennis J, Tyrer JP, Zamora MP, Arias-Perez JI, González-Neira A, Pita G, Alonso MR, Wang Q, Bolla MK, Czene K, Eriksson M, Humphreys K, Darabi H, Li J, Anton-Culver H, Neuhausen SL, Ziogas A, Clarke CA, Hopper JL, Dite GS, Apicella C, Southey MC, Chenevix-Trench G, Swerdlow A, Ashworth A, Orr N, Schoemaker M, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Bojesen SE, Nordestgaard BG, Flyger H, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Wang X, Olson JE, Vachon C, Purrington K, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Dunning AM, Shah M, Guénel P, Truong T, Sanchez M, Mulot C, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Lindblom A, Margolin S, Hooning MJ, Hollestelle A, Collée JM, Jager A, Cox A, Brock IW, Reed MW, Devilee P, Tollenaar RA, Seynaeve C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Dumont M, Soucy P, Dörk T, Bogdanova NV, Hamann U, Försti A, Rüdiger T, Ulmer HU, Fasching PA, Häberle L, Ekici AB, Beckmann MW, Fletcher O, Johnson N, dos Santos Silva I, Peto J, Radice P, Peterlongo P, Peissel B, Mariani P, Giles GG, Severi G, Baglietto L, Sawyer E, Tomlinson I, Kerin M, Miller N, Marme F, Burwinkel B, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Lambrechts D, Yesilyurt BT, Floris G, Leunen K, Alnæs GG, Kristensen V, Børresen-Dale AL, García-Closas M, Chanock SJ, Lissowska J, Figueroa JD, Schmidt MK, Broeks A, Verhoef S, Rutgers EJ, Brauch H, Brüning T, Ko YD, Couch FJ, Toland AE, Yannoukakos D, Pharoah PD, Hall P, Benítez J, Malats N, Easton DF. A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium. Hum Mol Genet 2014; 23:1934-46. [PMID: 24242184 PMCID: PMC3943524 DOI: 10.1093/hmg/ddt581] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2013] [Revised: 10/28/2013] [Accepted: 11/12/2013] [Indexed: 12/23/2022] Open
Abstract
Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.
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Affiliation(s)
- Roger L. Milne
- Human Cancer Genetics Programme and
- Centre for Epidemiology and Biostatistics, School of Population Health and
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Jesús Herranz
- Human Cancer Genetics Programme and
- Biostatistics Unit, IMDEA Food Institute, Madrid, Spain
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
| | - Jonathan P. Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - M. Pilar Zamora
- Servicio de Oncología Médica, Hospital Universitario La Paz, Madrid, Spain
| | | | - Anna González-Neira
- Human Genotyping-CEGEN Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Guillermo Pita
- Human Genotyping-CEGEN Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - M. Rosario Alonso
- Human Genotyping-CEGEN Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics
| | | | | | - Hatef Darabi
- Department of Medical Epidemiology and Biostatistics
| | - Jingmei Li
- Human Genetics Division, Genome Institute of Singapore, Singapore
| | - Hoda Anton-Culver
- Department of Epidemiology, University of California Irvine, Irvine, CA, USA
| | | | - Argyrios Ziogas
- Department of Epidemiology, University of California Irvine, Irvine, CA, USA
| | | | - John L. Hopper
- Centre for Epidemiology and Biostatistics, School of Population Health and
| | - Gillian S. Dite
- Centre for Epidemiology and Biostatistics, School of Population Health and
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, School of Population Health and
| | | | | | | | | | - Anthony Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
- Division of Breast Cancer Research
| | - Alan Ashworth
- Division of Breast Cancer Research
- Breakthrough Breast Cancer Research Centre and
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Nicholas Orr
- Division of Breast Cancer Research
- Breakthrough Breast Cancer Research Centre and
| | - Minouk Schoemaker
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Katarzyna Jaworska-Bieniek
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
- Postgraduate School of Molecular Medicine, Warsaw Medical University, Warsaw, Poland
| | - Katarzyna Durda
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Irene L. Andrulis
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics
| | - Julia A. Knight
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Division of Epidemiology, Dalla Lana School of Public Health and
| | - Gord Glendon
- Ontario Cancer Genetics Network, Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada
| | - Anna Marie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Stig E. Bojesen
- Copenhagen General Population Study
- Department of Clinical Biochemistry and
| | | | - Henrik Flyger
- Department of Breast Surgery, Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Taru A. Muranen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | | | - Carl Blomqvist
- Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland
| | | | | | | | - Dieter Flesch-Janys
- Department of Cancer Epidemiology/Clinical Cancer Registry and
- Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Xianshu Wang
- Department of Laboratory Medicine and Pathology and
| | - Janet E. Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu
| | | | - Mervi Grip
- Department of Surgery, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Pascal Guénel
- Inserm (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), U1018, Environmental Epidemiology of Cancer, Villejuif, France
- University Paris-Sud, UMRS 1018, Villejuif, France
| | - Thérèse Truong
- Inserm (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), U1018, Environmental Epidemiology of Cancer, Villejuif, France
- University Paris-Sud, UMRS 1018, Villejuif, France
| | - Marie Sanchez
- Inserm (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), U1018, Environmental Epidemiology of Cancer, Villejuif, France
- University Paris-Sud, UMRS 1018, Villejuif, France
| | - Claire Mulot
- Centre de Ressources Biologiques EPIGENETEC, Paris, France
- Inserm (National Institute of Health and Medical Research), U775, Paris, France
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Aida Karina Dieffenbach
- Division of Clinical Epidemiology and Aging Research
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research
| | | | | | - Sara Margolin
- Department of Oncology - Pathology, Karolinska Institutet, Stockholm, Sweden
| | | | | | - J. Margriet Collée
- Department of Clinical Genetics, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Agnes Jager
- Department of Medical Oncology, Family Cancer Clinic and
| | - Angela Cox
- CRUK/YCR Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Ian W. Brock
- CRUK/YCR Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Malcolm W.R. Reed
- CRUK/YCR Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Peter Devilee
- Department of Human Genetics
- Department of Pathology and
| | | | | | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Brian E. Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Fredrick Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Jacques Simard
- Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Quebec Research Center and Laval University, Quebec, Canada
| | - Martine Dumont
- Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Quebec Research Center and Laval University, Quebec, Canada
| | - Penny Soucy
- Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Quebec Research Center and Laval University, Quebec, Canada
| | - Thilo Dörk
- Department of Obstetrics and Gynaecology and
| | - Natalia V. Bogdanova
- Department of Obstetrics and Gynaecology and
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
| | - Asta Försti
- Division of Molecular Genetic Epidemiology and
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Thomas Rüdiger
- Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | | | - Peter A. Fasching
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Lothar Häberle
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Arif B. Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Matthias W. Beckmann
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | | | | | | | - Julian Peto
- London School of Hygiene and Tropical Medicine, London, UK
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine and
| | - Paolo Peterlongo
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Bernard Peissel
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Paolo Mariani
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
- Cogentech Cancer Genetic Test Laboratory, Milan, Italy
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, School of Population Health and
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Gianluca Severi
- Centre for Epidemiology and Biostatistics, School of Population Health and
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Laura Baglietto
- Centre for Epidemiology and Biostatistics, School of Population Health and
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Elinor Sawyer
- Division of Cancer Studies, NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas’ NHS Foundation Trust in Partnership with King's College London, London, UK
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics and
- Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Michael Kerin
- School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Ireland
| | - Nicola Miller
- School of Medicine, Clinical Science Institute, National University of Ireland, Galway, Ireland
| | - Federik Marme
- Department of Obstetrics and Gynecology and
- National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany
| | - Barbara Burwinkel
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Obstetrics and Gynecology and
| | - Arto Mannermaa
- Department of Clinical Pathology and
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine and
- Biocenter Kuopio, University of Eastern Finland, Kuopio, Finland
| | - Vesa Kataja
- Cancer Center, Kuopio University Hospital, Kuopio, Finland
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine and
- Biocenter Kuopio, University of Eastern Finland, Kuopio, Finland
| | - Veli-Matti Kosma
- Department of Clinical Pathology and
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine and
- Biocenter Kuopio, University of Eastern Finland, Kuopio, Finland
| | - Jaana M. Hartikainen
- Department of Clinical Pathology and
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine and
- Biocenter Kuopio, University of Eastern Finland, Kuopio, Finland
| | | | | | - Giuseppe Floris
- Multidisciplinary Breast Center, University Hospital Gasthuisberg, Leuven, Belgium
| | - Karin Leunen
- Multidisciplinary Breast Center, University Hospital Gasthuisberg, Leuven, Belgium
| | - Grethe Grenaker Alnæs
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
| | - Vessela Kristensen
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
- Faculty of Medicine (Faculty Division Ahus), UiO, Oslo, Norway
| | - Anne-Lise Børresen-Dale
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
- Faculty of Medicine (Faculty Division Ahus), UiO, Oslo, Norway
| | - Montserrat García-Closas
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
- Division of Breast Cancer Research
- Breakthrough Breast Cancer Research Centre and
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Memorial Cancer Center & Institute of Oncology, Warsaw, Poland
| | - Jonine D. Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Marjanka K. Schmidt
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Annegien Broeks
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Senno Verhoef
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Emiel J. Rutgers
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Hiltrud Brauch
- University of Tübingen, Tübingen, Germany
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr-University Bochum (IPA), Bochum, Germany
| | - Yon-Dschun Ko
- Department of Internal Medicine, Evangelische Kliniken Bonn GmbH, Johanniter Krankenhaus, Bonn, Germany
| | - The GENICA Network
- Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
- University of Tübingen, Tübingen, Germany
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr-University Bochum (IPA), Bochum, Germany
- Department of Internal Medicine, Evangelische Kliniken Bonn GmbH, Johanniter Krankenhaus, Bonn, Germany
- Institute for Occupational Medicine and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute of Pathology, Medical Faculty of the University of Bonn, Bonn, Germany
| | | | - Amanda E. Toland
- Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - The TNBCC
- Department of Laboratory Medicine and Pathology and
| | - Drakoulis Yannoukakos
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research ‘Demokritos’, Athens, Greece
| | - Paul D.P. Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics
| | - Javier Benítez
- Human Cancer Genetics Programme and
- Human Genotyping-CEGEN Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain
| | | | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
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Van den Broeck T, Joniau S, Clinckemalie L, Helsen C, Prekovic S, Spans L, Tosco L, Van Poppel H, Claessens F. The role of single nucleotide polymorphisms in predicting prostate cancer risk and therapeutic decision making. BIOMED RESEARCH INTERNATIONAL 2014; 2014:627510. [PMID: 24701578 PMCID: PMC3950427 DOI: 10.1155/2014/627510] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Accepted: 01/07/2014] [Indexed: 12/20/2022]
Abstract
Prostate cancer (PCa) is a major health care problem because of its high prevalence, health-related costs, and mortality. Epidemiological studies have suggested an important role of genetics in PCa development. Because of this, an increasing number of single nucleotide polymorphisms (SNPs) had been suggested to be implicated in the development and progression of PCa. While individual SNPs are only moderately associated with PCa risk, in combination, they have a stronger, dose-dependent association, currently explaining 30% of PCa familial risk. This review aims to give a brief overview of studies in which the possible role of genetic variants was investigated in clinical settings. We will highlight the major research questions in the translation of SNP identification into clinical practice.
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Affiliation(s)
- Thomas Van den Broeck
- Department of Urology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
| | - Steven Joniau
- Department of Urology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Liesbeth Clinckemalie
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
| | - Christine Helsen
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
| | - Stefan Prekovic
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
| | - Lien Spans
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
| | - Lorenzo Tosco
- Department of Urology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Hendrik Van Poppel
- Department of Urology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Frank Claessens
- Laboratory of Molecular Endocrinology, Department of Cellular and Molecular Medicine, KU Leuven, Campus Gasthuisberg O&N1, P.O. Box 901, Herestraat 49, 3000 Leuven, Belgium
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10
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Su WH, Yao Shugart Y, Chang KP, Tsang NM, Tse KP, Chang YS. How genome-wide SNP-SNP interactions relate to nasopharyngeal carcinoma susceptibility. PLoS One 2013; 8:e83034. [PMID: 24376627 PMCID: PMC3871583 DOI: 10.1371/journal.pone.0083034] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Accepted: 10/29/2013] [Indexed: 11/18/2022] Open
Abstract
This study is the first to use genome-wide association study (GWAS) data to evaluate the multidimensional genetic architecture underlying nasopharyngeal cancer. Since analysis of data from GWAS confirms a close and consistent association between elevated risk for nasopharyngeal carcinoma (NPC) and major histocompatibility complex class 1 genes, our goal here was to explore lesser effects of gene-gene interactions. We conducted an exhaustive genome-wide analysis of GWAS data of NPC, revealing two-locus interactions occurring between single nucleotide polymorphisms (SNPs), and identified a number of suggestive interaction loci which were missed by traditional GWAS analyses. Although none of the interaction pairs we identified passed the genome-wide Bonferroni-adjusted threshold for significance, using independent GWAS data from the same population (Stage 2), we selected 66 SNP pairs in 39 clusters with P<0.01. We identified that in several chromosome regions, multiple suggestive interactions group to form a block-like signal, effectively reducing the rate of false discovery. The strongest cluster of interactions involved the CREB5 gene and a SNP rs1607979 on chromosome 17q22 (P = 9.86×10(-11)) which also show trans-expression quantitative loci (eQTL) association in Chinese population. We then detected a complicated cis-interaction pattern around the NPC-associated HLA-B locus, which is immediately adjacent to copy-number variations implicated in male susceptibility for NPC. While it remains to be seen exactly how and to what degree SNP-SNP interactions such as these affect susceptibility for nasopharyngeal cancer, future research on these questions holds great promise for increasing our understanding of this disease's genetic etiology, and possibly also that of other gene-related cancers.
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Affiliation(s)
- Wen-Hui Su
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Yin Yao Shugart
- Genomic Research Branch, Division of Neuroscience and Behavioral Sciences, National Institute of Mental Health, NIH, Bethesda, Maryland, United States of America
- Department of Gastroenterology, Johns Hopkins Medical School, Baltimore, Maryland, United States of America
| | - Kai-Ping Chang
- Department of Otolaryngology - Head and Neck Surgery, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan
| | - Ngan-Ming Tsang
- Department of Radiation Oncology, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan
| | - Ka-Po Tse
- Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Yu-Sun Chang
- Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan
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11
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Chu M, Zhang R, Zhao Y, Wu C, Guo H, Zhou B, Lu J, Shi Y, Dai J, Jin G, Ma H, Dong J, Wei Y, Wang C, Gong J, Sun C, Zhu M, Qiu Y, Wu T, Hu Z, Lin D, Shen H, Chen F. A genome-wide gene-gene interaction analysis identifies an epistatic gene pair for lung cancer susceptibility in Han Chinese. Carcinogenesis 2013; 35:572-7. [PMID: 24325914 DOI: 10.1093/carcin/bgt400] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide. By now, genome-wide association studies (GWAS) have identified numerous loci associated with the risk of developing lung cancer. However, these loci account for only a small fraction of the familial lung cancer risk. We hypothesized that epistasis may contribute to the missing heritability. To test this hypothesis, we systematically evaluated the association of epistasis of genetic variants with risk of lung cancer in Han Chinese cohorts. We conducted a pairwise genetic interaction analysis of 591370 variants, using BOolean Operation-based Screening and Testing (BOOST), in an ongoing GWAS of lung cancer that includes 2331 cases and 3077 controls. Pairs of epistatic loci with P BOOST ≤ 1.00×10(-6) were further evaluated by a logistic regression model (LRM) with covariate adjustment. Four promising epistatic pairs identified at the screening stage (P LRM ≤ 2.86×10(-) (13)) were validated in two replication cohorts: the first from Beijing (1534 cases and 1489 controls) and the second from Shenyang and Guangzhou (2512 cases and 2449 controls). Using this combined analysis, we identified an interaction between rs2562796 and rs16832404 at 2p32.2 that was significantly associated with the risk of developing lung cancer (P LRM = 1.03×10(-13) in total 13 392 subjects). This study is the first investigation of epistasis for lung cancer on a genome-wide scale in Han Chinese. It addresses part of the missing heritability in lung cancer risk and provides novel insight into the multifactorial etiology of lung cancer.
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Affiliation(s)
- Minjie Chu
- Department of Epidemiology and Biostatistics and Ministry of Education (MOE), Key Laboratory for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
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Dasgupta S, Reddy BM. The Role of Epistasis in the Etiology of Polycystic Ovary Syndrome among Indian Women: SNP-SNP and SNP-Environment Interactions. Ann Hum Genet 2013; 77:288-98. [DOI: 10.1111/ahg.12020] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Accepted: 01/28/2013] [Indexed: 11/28/2022]
Affiliation(s)
- Shilpi Dasgupta
- Molecular Anthropology Group; Biological Anthropology Unit, Indian Statistical Institute; Hyderabad, Andhra Pradesh India
| | - B. Mohan Reddy
- Molecular Anthropology Group; Biological Anthropology Unit, Indian Statistical Institute; Hyderabad, Andhra Pradesh India
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Jiao S, Hsu L, Berndt S, Bézieau S, Brenner H, Buchanan D, Caan BJ, Campbell PT, Carlson CS, Casey G, Chan AT, Chang-Claude J, Chanock S, Conti DV, Curtis KR, Duggan D, Gallinger S, Gruber SB, Harrison TA, Hayes RB, Henderson BE, Hoffmeister M, Hopper JL, Hudson TJ, Hutter CM, Jackson RD, Jenkins MA, Kantor ED, Kolonel LN, Küry S, Le Marchand L, Lemire M, Newcomb PA, Potter JD, Qu C, Rosse SA, Schoen RE, Schumacher FR, Seminara D, Slattery ML, Ulrich CM, Zanke BW, Peters U. Genome-wide search for gene-gene interactions in colorectal cancer. PLoS One 2012; 7:e52535. [PMID: 23300701 PMCID: PMC3530500 DOI: 10.1371/journal.pone.0052535] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2012] [Accepted: 11/15/2012] [Indexed: 12/28/2022] Open
Abstract
Genome-wide association studies (GWAS) have successfully identified a number of single-nucleotide polymorphisms (SNPs) associated with colorectal cancer (CRC) risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG) is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI). With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10−4). For the known locus rs10795668 (10p14), we found an interacting SNP rs367615 (5q21) with replication p = 0.01 and combined p = 4.19×10−8. Among the top marginal SNPs after LD pruning (n = 163), we identified an interaction between rs1571218 (20p12.3) and rs10879357 (12q21.1) (nominal combined p = 2.51×10−6; Bonferroni adjusted p = 0.03). Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.
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Affiliation(s)
- Shuo Jiao
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
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