A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts
The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years....
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| Published in | PloS one Vol. 12; no. 3; p. e0173997 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
16.03.2017
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0173997 |
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| Abstract | The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. |
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| AbstractList | The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79–2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 ([beta] = 0.45, p = 3.48x10.sup.-22 ), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10.sup.-15 ), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 ([Beta] = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. |
| Audience | Academic |
| Author | Cornelis, Marilyn Aschard, Hugues Pasquale, Louis R. Tworoger, Shelley S. Huang, Hongyan Curhan, Gary Hu, Frank Loomis, Stephanie Huang, Jinyan Liang, Liming Kang, Jae H. Rimm, Eric Tamimi, Rulla M. Choi, Hyon Jensen, Majken De Vivo, Immaculata Kabrhel, Christopher Hunter, David J. Lindström, Sara Gaziano, Michael Kraft, Peter Chan, Andrew T. Stampfer, Meir J. Eliassen, A. Heather Turman, Constance Fuchs, Charles Hankinson, Susan E. Wiggs, Janey L. |
| AuthorAffiliation | 5 Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, United States of America 2 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America 4 Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA, United States of America 11 Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States of America 12 Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, United States of America 13 Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America 3 Department of Epidemiology, University of Washington, Seattle, WA, United States of America 6 Section of Rheumatology and Clinical Epidemiology Unit, Boston University School of Medicine, Boston, MA, United States of America 14 Department of Emergency Medicine, Center for Vascular Emergencies, Massachusetts General Hospital, Harvard M |
| AuthorAffiliation_xml | – name: Children's National Health System, UNITED STATES – name: 4 Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA, United States of America – name: 3 Department of Epidemiology, University of Washington, Seattle, WA, United States of America – name: 10 Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America – name: 9 Renal Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States of America – name: 7 Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America – name: 6 Section of Rheumatology and Clinical Epidemiology Unit, Boston University School of Medicine, Boston, MA, United States of America – name: 13 Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America – name: 2 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America – name: 5 Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, United States of America – name: 11 Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States of America – name: 15 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America – name: 12 Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, United States of America – name: 8 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States of America – name: 1 Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America – name: 14 Department of Emergency Medicine, Center for Vascular Emergencies, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2017 Public Library of Science 2017 Lindström et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Attribution 2017 Lindström et al 2017 Lindström et al |
| Copyright_xml | – notice: COPYRIGHT 2017 Public Library of Science – notice: 2017 Lindström et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: Attribution – notice: 2017 Lindström et al 2017 Lindström et al |
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| DOI | 10.1371/journal.pone.0173997 |
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| DocumentTitleAlternate | A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 PMCID: PMC5354293 Conceptualization: PK.Data curation: S. Loomis CT HH JH MC MJ.Formal analysis: S. Lindström S. Loomis CT HH JH HA MC MJ.Funding acquisition: S. Lindström ATC HC GC IDV AHE CF MG SEH FH JHK CK LRP ER MJS RMT SST JLW DJH.Methodology: PK.Resources: ATC HC GC IDV AHE CF MG SEH FH JHK CK LRP ER MJS RMT SST JLW DJH.Supervision: PK.Visualization: S. Lindström CT HH.Writing – original draft: S. Lindström PK.Writing – review & editing: S. Lindström S. Loomis CT HH JH HA ATC HC MC GC IDV AHE CF MG SEH FH MJ JHK CK LL LRP ER MJS RMT SST JLW DJH PK. Competing Interests: The authors have declared that no competing interests exist. |
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| Snippet | The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have... The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have... |
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| SubjectTerms | ABO system Alpha-Ketoglutarate-Dependent Dioxygenase FTO Alpha-Ketoglutarate-Dependent Dioxygenase FTO - genetics Analysis Applications Bioinformatics Biology and Life Sciences Body mass Body Mass Index Body size Care and treatment Cohort Studies Computer Science Data processing Deoxyribonucleic acid Diabetes DNA Epidemiology Genetic aspects Genetic diversity Genetic Variation Genetics Genome-wide association studies Genome-Wide Association Study Genomes Genotype-environment interactions Genotypes Health care Hospitals Human genetics Humans Life Sciences Medical personnel Medical schools Medicine and Health Sciences Methodology Nurses Nutrition People and Places Physicians Polymorphism, Single Nucleotide Preventive medicine Principal components analysis Public health Research and Analysis Methods Santé publique et épidémiologie Single-nucleotide polymorphism Statistics Studies Surveys Thromboembolism Venous Thromboembolism Venous Thromboembolism - genetics Womens health |
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| Title | A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts |
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