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Russo A, Lee JK, Pasquina LW, Del Re M, Dilks HH, Murugesan K, Madison RW, Lee Y, Schrock AB, Comment L, Dietrich M, Oxnard GR, Rolfo C. Liquid Biopsy of Lung Cancer Before Pathological Diagnosis Is Associated With Shorter Time to Treatment. JCO Precis Oncol 2024; 8:e2300535. [PMID: 38295321 PMCID: PMC10843270 DOI: 10.1200/po.23.00535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/31/2023] [Accepted: 11/17/2023] [Indexed: 02/02/2024] Open
Abstract
PURPOSE Studies have investigated the early use of liquid biopsy (LBx) during the diagnostic workup of patients presenting with clinical evidence of advanced lung cancer, but real-world adoption and impact has not been characterized. The aim of this study was to determine whether the use of LBx before diagnosis (Dx; LBx-Dx) enables timely comprehensive genomic profiling (CGP) and shortens time until treatment initiation for advanced non-small-cell lung cancer (aNSCLC). MATERIALS AND METHODS This study used the Flatiron Health-Foundation Medicine electronic health record-derived deidentified clinicogenomic database of patients with aNSCLC from approximately 280 US cancer clinics. RESULTS Of 1,076 patients with LBx CGP ordered within 30 days prediagnosis/postdiagnosis, we focused on 56 (5.2%) patients who ordered LBx before diagnosis date (median 8 days between order and diagnosis, range, 1-28). Compared with 1,020 patients who ordered LBx after diagnosis (Dx-LBx), LBx-Dx patients had similar stage and ctDNA tumor fraction (TF). LBx-Dx patients received CGP results a median of 1 day after Dx versus 25 days for Dx-LBx patients. Forty-three percent of LBx-Dx were positive for an National Comprehensive Cancer Network driver, and 32% had ctDNA TF >1% but were driver negative (presumed true negatives). In 748 patients with previously untreated aNSCLC, median time from Dx to therapy was shorter in the LBx-Dx versus Dx-LBx group (21 v 35 days; P < .001). CONCLUSION Early LBx in anticipation of pathologic diagnosis of aNSCLC was uncommon in this real-world cohort, yet this emerging paradigm was associated with an abbreviated time to CGP results and faster therapy initiation. Forthcoming prospective studies will clarify the utility of LBx in parallel with biopsy for diagnostic confirmation for patients presenting with suspected advanced lung cancer.
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Affiliation(s)
- Alessandro Russo
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Onco-hematology, Papardo Hospital, Messina, Italy
| | | | | | - Marzia Del Re
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
- Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | | | | | - Yi Lee
- Trinity Health Oakland, Pontiac, MI
- Wayne State University School of Medicine, Detroit, MI
| | | | | | - Martin Dietrich
- Florida Cancer Specialists & Research Institute, Lake Mary, FL
| | | | - Christian Rolfo
- Center for Thoracic Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
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Affiliation(s)
| | - Holli H Dilks
- a Sarah Cannon Research Institute , Nashville , Tennessee , USA
| | - Suzanne F Jones
- a Sarah Cannon Research Institute , Nashville , Tennessee , USA
| | - Howard Burris
- a Sarah Cannon Research Institute , Nashville , Tennessee , USA
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3
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Gong J, Nishimura KK, Fernandez-Rhodes L, Haessler J, Bien S, Graff M, Lim U, Lu Y, Gross M, Fornage M, Yoneyama S, Isasi CR, Buzkova P, Daviglus M, Lin DY, Tao R, Goodloe R, Bush WS, Farber-Eger E, Boston J, Dilks HH, Ehret G, Gu CC, Lewis CE, Nguyen KDH, Cooper R, Leppert M, Irvin MR, Bottinger EP, Wilkens LR, Haiman CA, Park L, Monroe KR, Cheng I, Stram DO, Carlson CS, Jackson R, Kuller L, Houston D, Kooperberg C, Buyske S, Hindorff LA, Crawford DC, Loos RJ, Le Marchand L, Matise TC, North KE, Peters U. Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI. Int J Obes (Lond) 2018; 42:384-390. [PMID: 29381148 PMCID: PMC5876082 DOI: 10.1038/ijo.2017.304] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 11/03/2017] [Accepted: 11/21/2017] [Indexed: 01/05/2023]
Abstract
OBJECTIVE Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population. SUBJECTS Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models. RESULTS We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue. CONCLUSION Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
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Affiliation(s)
- Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Katherine K. Nishimura
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Lindsay Fernandez-Rhodes
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jeffery Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Misa Graff
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Unhee Lim
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Myron Gross
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Myriam Fornage
- Health Science Center, University of Texas, Austin, Texas, United States of America
| | - Sachiko Yoneyama
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Martha Daviglus
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, U United States of America SA
| | - Dan-Yu Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ran Tao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - William S. Bush
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Eric Farber-Eger
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Jonathan Boston
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Holli H. Dilks
- Sarah Cannon Research Institute, Nashville, Tennessee, United States of America
| | - Georg Ehret
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Division of Cardiology, Geneva University Hospital, Geneva, Switzerland
| | - C. Charles Gu
- Department of Biostatistics, Washington University, St. Louis, Missouri, United States of America
| | - Cora E. Lewis
- Department of Medicine, University of Alabama, Birmingham, Alabama, United States of America
| | - Khanh-Dung H. Nguyen
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Richard Cooper
- Preventive Medicine and Epidemiology, Loyola University, Chicago, Illinois, United States of America
| | - Mark Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama, Birmingham, Alabama, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Lynne R. Wilkens
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Christopher A. Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Lani Park
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Kristine R. Monroe
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Iona Cheng
- Cancer Prevention Institute of California, Fremont, California, United States of America
| | - Daniel O. Stram
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Christopher S. Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Rebecca Jackson
- Department of Internal Medicine, Ohio State Medical Center, Columbus, Ohio, United States of America
| | - Lew Kuller
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Denise Houston
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Steven Buyske
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Lucia A. Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Dana C. Crawford
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Loic Le Marchand
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Tara C. Matise
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Kari E. North
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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Oetjens MT, Bush WS, Denny JC, Birdwell K, Kodaman N, Verma A, Dilks HH, Pendergrass SA, Ritchie MD, Crawford DC. Evidence for extensive pleiotropy among pharmacogenes. Pharmacogenomics 2016; 17:853-66. [PMID: 27249515 DOI: 10.2217/pgs-2015-0007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
AIM We sought to identify potential pleiotropy involving pharmacogenes. METHODS We tested 184 functional variants in 34 pharmacogenes for associations using a custom grouping of International Classification and Disease, Ninth Revision billing codes extracted from deidentified electronic health records of 6892 patients. RESULTS We replicated several associations including ABCG2 (rs2231142) and gout (p = 1.73 × 10(-7); odds ratio [OR]: 1.73; 95% CI: 1.40-2.12); and SLCO1B1 (rs4149056) and jaundice (p = 2.50 × 10(-4); OR: 1.67; 95% CI: 1.27-2.20). CONCLUSION In this systematic screen for phenotypic associations with functional variants, several novel genotype-phenotype combinations also achieved phenome-wide significance, including SLC15A2 rs1143672 and renal osteodystrophy (p = 2.67 × 10(-) (6); OR: 0.61; 95% CI: 0.49-0.75).
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Affiliation(s)
- Matthew T Oetjens
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - William S Bush
- Department of Epidemiology & Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37203, USA
| | - Kelly Birdwell
- Department of Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Nuri Kodaman
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Anurag Verma
- Center for Systems Genomics, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Holli H Dilks
- Sarah Cannon Research Institute, Nashville, TN 37203 USA
| | - Sarah A Pendergrass
- Center for Systems Genomics, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Marylyn D Ritchie
- Center for Systems Genomics, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Dana C Crawford
- Department of Epidemiology & Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
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Oetjens MT, Brown-Gentry K, Goodloe R, Dilks HH, Crawford DC. Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data. Front Genet 2016; 7:76. [PMID: 27200085 PMCID: PMC4858524 DOI: 10.3389/fgene.2016.00076] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Accepted: 04/18/2016] [Indexed: 01/01/2023] Open
Abstract
Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991–1994 (NHANES III, phase 2) and 1999–2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999–2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype–phenotype studies but are sans genome-wide data.
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Affiliation(s)
- Matthew T Oetjens
- Center for Human Genetics Research Vanderbilt University, Nashville TN, USA
| | | | - Robert Goodloe
- Center for Human Genetics Research Vanderbilt University, Nashville TN, USA
| | | | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland OH, USA
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Kocarnik JM, Park SL, Han J, Dumitrescu L, Cheng I, Wilkens LR, Schumacher FR, Kolonel L, Carlson CS, Crawford DC, Goodloe RJ, Dilks HH, Baker P, Richardson D, Matise TC, Ambite JL, Song F, Qureshi AA, Zhang M, Duggan D, Hutter C, Hindorff L, Bush WS, Kooperberg C, Le Marchand L, Peters U. Pleiotropic and sex-specific effects of cancer GWAS SNPs on melanoma risk in the population architecture using genomics and epidemiology (PAGE) study. PLoS One 2015; 10:e0120491. [PMID: 25789475 PMCID: PMC4366224 DOI: 10.1371/journal.pone.0120491] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 01/22/2015] [Indexed: 11/19/2022] Open
Abstract
Background Several regions of the genome show pleiotropic associations with multiple cancers. We sought to evaluate whether 181 single-nucleotide polymorphisms previously associated with various cancers in genome-wide association studies were also associated with melanoma risk. Methods We evaluated 2,131 melanoma cases and 20,353 controls from three studies in the Population Architecture using Genomics and Epidemiology (PAGE) study (EAGLE-BioVU, MEC, WHI) and two collaborating studies (HPFS, NHS). Overall and sex-stratified analyses were performed across studies. Results We observed statistically significant associations with melanoma for two lung cancer SNPs in the TERT-CLPTM1L locus (Bonferroni-corrected p<2.8x10-4), replicating known pleiotropic effects at this locus. In sex-stratified analyses, we also observed a potential male-specific association between prostate cancer risk variant rs12418451 and melanoma risk (OR=1.22, p=8.0x10-4). No other variants in our study were associated with melanoma after multiple comparisons adjustment (p>2.8e-4). Conclusions We provide confirmatory evidence of pleiotropic associations with melanoma for two SNPs previously associated with lung cancer, and provide suggestive evidence for a male-specific association with melanoma for prostate cancer variant rs12418451. This SNP is located near TPCN2, an ion transport gene containing SNPs which have been previously associated with hair pigmentation but not melanoma risk. Previous evidence provides biological plausibility for this association, and suggests a complex interplay between ion transport, pigmentation, and melanoma risk that may vary by sex. If confirmed, these pleiotropic relationships may help elucidate shared molecular pathways between cancers and related phenotypes.
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Affiliation(s)
- Jonathan M. Kocarnik
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- * E-mail:
| | - S. Lani Park
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana, United States of America
| | - Logan Dumitrescu
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Iona Cheng
- Cancer Prevention Institute of California, Fremont, California, United States of America
| | - Lynne R. Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Fredrick R. Schumacher
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Laurence Kolonel
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Chris S. Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Dana C. Crawford
- Department of Epidemiology, Case Western Reserve University, Cleveland, Ohio, United States of America
- Biostatistics Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Robert J. Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Holli H. Dilks
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Paxton Baker
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Danielle Richardson
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Tara C. Matise
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
| | - José Luis Ambite
- Information Sciences Institute, University of Southern California, Marina del Rey, California, United States of America
| | - Fengju Song
- Department of Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, People’s Republic of China
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Abrar A. Qureshi
- Department of Dermatology, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Mingfeng Zhang
- Department of Dermatology, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - David Duggan
- Translational Genomics Research Institute, Phoenix, Arizona, United States of America
| | - Carolyn Hutter
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, NCI, NIH, Bethesda, Maryland, United States of America
| | - Lucia Hindorff
- Division of Genomic Medicine, NHGRI, NIH, Bethesda, Maryland, Untied States of America
| | - William S. Bush
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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Jeff JM, Brown-Gentry K, Goodloe R, Ritchie MD, Denny JC, Kho AN, Armstrong LL, McClellan B, Mayo P, Allen M, Jin H, Gillani NB, Schnetz-Boutaud N, Dilks HH, Basford MA, Pacheco JA, Jarvik GP, Chisholm RL, Roden DM, Hayes MG, Crawford DC. Replication of SCN5A Associations with Electrocardio-graphic Traits in African Americans from Clinical and Epidemiologic Studies. Evol Comput Mach Learn Data Min Bioinform 2015; 2014:939-951. [PMID: 25590050 PMCID: PMC4290789 DOI: 10.1007/978-3-662-45523-4_76] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The NAv1.5 sodium channel α subunit is the predominant α-subunit expressed in the heart and is associated with cardiac arrhythmias. We tested five previously identified SCN5A variants (rs7374138, rs7637849, rs7637849, rs7629265, and rs11129796) for an association with PR interval and QRS duration in two unique study populations: the Third National Health and Nutrition Examination Survey (NHANES III, n= 552) accessed by the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) and a combined dataset (n= 455) from two biobanks linked to electronic medical records from Vanderbilt University (BioVU) and Northwestern University (NUgene) as part of the electronic Medical Records & Genomics (eMERGE) network. A meta-analysis including all three study populations (n~4,000) suggests that eight SCN5A associations were significant for both QRS duration and PR interval (p<5.0E-3) with little evidence for heterogeneity across the study populations. These results suggest that published SCN5A associations replicate across different study designs in a meta-analysis and represent an important first step in utility of multiple study designs for genetic studies and the identification/characterization of genetic variants associated with ECG traits in African-descent populations.
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Affiliation(s)
- Janina M. Jeff
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kristin Brown-Gentry
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Marylyn D. Ritchie
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Joshua C. Denny
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA
| | - Abel N. Kho
- Division of General Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Loren L. Armstrong
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Bob McClellan
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Ping Mayo
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Melissa Allen
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Hailing Jin
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Niloufar B. Gillani
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | | | - Holli H. Dilks
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Melissa A. Basford
- Office of Personalized Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Jennifer A. Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Gail P. Jarvik
- University of Washington Medical Center, Seattle, WA 98195, USA
| | - Rex L. Chisholm
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Dan M. Roden
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
- Office of Personalized Medicine, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Dana C. Crawford
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
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Crawford DC, Dumitrescu L, Goodloe R, Brown-Gentry K, Boston J, McClellan B, Sutcliffe C, Wiseman R, Baker P, Pericak-Vance MA, Scott WK, Allen M, Mayo P, Schnetz-Boutaud N, Dilks HH, Haines JL, Pollin TI. Rare variant APOC3 R19X is associated with cardio-protective profiles in a diverse population-based survey as part of the Epidemiologic Architecture for Genes Linked to Environment Study. ACTA ACUST UNITED AC 2014; 7:848-53. [PMID: 25363704 DOI: 10.1161/circgenetics.113.000369] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND A founder mutation was recently discovered and described as conferring favorable lipid profiles and reduced subclinical atherosclerotic disease in a Pennsylvania Amish population. Preliminary data have suggested that this null mutation APOC3 R19X (rs76353203) is rare in the general population. METHODS AND RESULTS To better describe the frequency and lipid profile in the general population, we as part of the Population Architecture using Genomics and Epidemiology I Study and the Epidemiological Architecture for Genes Linked to Environment Study genotyped rs76353203 in 1113 Amish participants from Ohio and Indiana and 19 613 participants from the National Health and Nutrition Examination Surveys (NHANES III, 1999 to 2002, and 2007 to 2008). We found no carriers among the Ohio and Indiana Amish. Of the 19 613 NHANES participants, we identified 31 participants carrying the 19X allele, for an overall allele frequency of 0.08%. Among fasting adults, the 19X allele was associated with lower triglycerides (n=7603; β=-71.20; P=0.007) and higher high-density lipoprotein cholesterol (n=8891; β=15.65; P=0.0002) and, although not significant, lower low-density lipoprotein cholesterol (n=6502; β= -4.85; P=0.68) after adjustment for age, sex, and race/ethnicity. On average, 19X allele participants had approximately half the triglyceride levels (geometric means, 51.3 to 69.7 versus 134.6 to 141.3 mg/dL), >20% higher high-density lipoprotein cholesterol levels (geometric means, 56.8 to 74.4 versus 50.38 to 53.36 mg/dL), and lower low-density lipoprotein cholesterol levels (geometric means, 104.5 to 128.6 versus 116.1 to 125.7 mg/dL) compared with noncarrier participants. CONCLUSIONS These data demonstrate that APOC3 19X exists in the general US population in multiple racial/ethnic groups and is associated with cardio-protective lipid profiles.
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Affiliation(s)
- Dana C Crawford
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.).
| | - Logan Dumitrescu
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Robert Goodloe
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Kristin Brown-Gentry
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Jonathan Boston
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Bob McClellan
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Cara Sutcliffe
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Rachel Wiseman
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Paxton Baker
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Margaret A Pericak-Vance
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - William K Scott
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Melissa Allen
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Ping Mayo
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Nathalie Schnetz-Boutaud
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Holli H Dilks
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Jonathan L Haines
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
| | - Toni I Pollin
- From the Institute for Computational Biology (D.C.C., P.M., J.L.H.), Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH (D.C.C., J.L.H.); Center for Human Genetics Research (L.D., R.G., K.B.-G., J.B., B.M., M.A., N.S.-B.), Department of Molecular Physiology and Biophysics (L.D.), Vanderbilt Technologies for Advanced Genomics Core Facility, Vanderbilt University, Nashville, TN (C.S., R.W., P.B., H.H.D.); Hussman Institute for Human Genomics, University of Miami, FL (M.A.P.-V., W.K.S.); and Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (T.I.P.)
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9
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Hall JB, Dumitrescu L, Dilks HH, Crawford DC, Bush WS. Accuracy of administratively-assigned ancestry for diverse populations in an electronic medical record-linked biobank. PLoS One 2014; 9:e99161. [PMID: 24896101 PMCID: PMC4045967 DOI: 10.1371/journal.pone.0099161] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2014] [Accepted: 05/12/2014] [Indexed: 11/19/2022] Open
Abstract
Recently, the development of biobanks linked to electronic medical records has presented new opportunities for genetic and epidemiological research. Studies based on these resources, however, present unique challenges, including the accurate assignment of individual-level population ancestry. In this work we examine the accuracy of administratively-assigned race in diverse populations by comparing assigned races to genetically-defined ancestry estimates. Using 220 ancestry informative markers, we generated principal components for patients in our dataset, which were used to cluster patients into groups based on genetic ancestry. Consistent with other studies, we find a strong overall agreement (Kappa = 0.872) between genetic ancestry and assigned race, with higher rates of agreement for African-descent and European-descent assignments, and reduced agreement for Hispanic, East Asian-descent, and South Asian-descent assignments. These results suggest caution when selecting study samples of non-African and non-European backgrounds when administratively-assigned race from biobanks is used.
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Affiliation(s)
- Jacob B. Hall
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Logan Dumitrescu
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Holli H. Dilks
- Vanderbilt Technologies for Advanced Genomics (VANTAGE), Vanderbilt University, Nashville, Tennessee, United States of America
| | - Dana C. Crawford
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - William S. Bush
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
- * E-mail:
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10
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Cheng I, Kocarnik JM, Dumitrescu L, Lindor NM, Chang-Claude J, Avery CL, Caberto CP, Love SA, Slattery ML, Chan AT, Baron JA, Hindorff LA, Park SL, Schumacher FR, Hoffmeister M, Kraft P, Butler A, Duggan D, Hou L, Carlson CS, Monroe KR, Lin Y, Carty CL, Mann S, Ma J, Giovannucci EL, Fuchs CS, Newcomb PA, Jenkins MA, Hopper JL, Haile RW, Conti DV, Campbell PT, Potter JD, Caan BJ, Schoen RE, Hayes RB, Chanock SJ, Berndt SI, Kury S, Bezieau S, Ambite JL, Kumaraguruparan G, Richardson D, Goodloe RJ, Dilks HH, Baker P, Zanke BW, Lemire M, Gallinger S, Hsu L, Jiao S, Harrison T, Seminara D, Haiman CA, Kooperberg C, Wilkens LR, Hutter CM, White E, Crawford DC, Heiss G, Hudson TJ, Brenner H, Bush WS, Casey G, Marchand LL, Peters U. Pleiotropic effects of genetic risk variants for other cancers on colorectal cancer risk: PAGE, GECCO and CCFR consortia. Gut 2014; 63:800-7. [PMID: 23935004 PMCID: PMC3918490 DOI: 10.1136/gutjnl-2013-305189] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. DESIGN We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10(-4) was used to determine statistical significance of the associations. RESULTS Two correlated SNPs--rs10090154 and rs4242382--in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10(-5)), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. CONCLUSIONS This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.
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Affiliation(s)
- Iona Cheng
- Cancer Prevention Institute of California, Fremont, CA, USA
| | - Jonathan M Kocarnik
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Logan Dumitrescu
- Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA,Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Noralane M Lindor
- Department of Health Science Research, Mayo Clinic Arizona, Arizona, USA
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Christy L. Avery
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Christian P Caberto
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Shelly-Ann Love
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Martha L Slattery
- Department of Internal Medicine, University of Utah Health Sciences Center, Salt Lake City, UT, USA
| | - Andrew T Chan
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard, Boston, MA, USA,Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
| | - John A Baron
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Lucia A Hindorff
- Office of Population Genomics, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sungshim Lani Park
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Fredrick R Schumacher
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Peter Kraft
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Anne Butler
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - David Duggan
- Division of Genetic Basis of Human Disease, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Chris S Carlson
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Kristine R Monroe
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Cara L Carty
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sue Mann
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jing Ma
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard, Boston, MA, USA
| | | | - Charles S Fuchs
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard, Boston, MA, USA,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mark A Jenkins
- Centre for Molecular, Environmental, Genetic & Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - John L Hopper
- Centre for Molecular, Environmental, Genetic & Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | | | - David V Conti
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peter T Campbell
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA
| | - John D Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Centre for Public Health Research, Massey University, Wellington, New Zealand
| | - Bette J Caan
- Division of Research, Kaiser Permanente, CA, USA
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, PA, USA
| | - Richard B Hayes
- Division of Epidemiology, Department of Environmental Medicine, New York University School of Medicine, New York, NY, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sebastien Kury
- Service de Génétique Médicale, CHU Nantes, Nantes, France
| | | | - Jose Luis Ambite
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
| | - Gowri Kumaraguruparan
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
| | | | - Robert J Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Holli H Dilks
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA,Vanderbilt Technologies for Advanced Genomics, Vanderbilt University, Nashville, TN, USA
| | - Paxton Baker
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Brent W Zanke
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Mathieu Lemire
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Steven Gallinger
- Samuel Lunenfeld Research Institute, Toronto, Ontario, Canada,Department of Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Shuo Jiao
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tabitha Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Daniela Seminara
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lynne R Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Carolyn M Hutter
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Emily White
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Dana C Crawford
- Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA,Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas J Hudson
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada,Department Molecular Genetics, University of Toronto, Toronto, Ontario, Canada,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany,Germany German Cancer Consortium (DKTK), Heidelberg, Germany
| | - William S Bush
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA,Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Graham Casey
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
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Oetjens MT, Denny JC, Ritchie MD, Gillani NB, Richardson DM, Restrepo NA, Pulley JM, Dilks HH, Basford MA, Bowton E, Masys DR, Wilke RA, Roden DM, Crawford DC. Assessment of a pharmacogenomic marker panel in a polypharmacy population identified from electronic medical records. Pharmacogenomics 2014; 14:735-44. [PMID: 23651022 DOI: 10.2217/pgs.13.64] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The ADME Core Panel assays 184 variants across 34 pharmacogenes, many of which are difficult to accurately genotype with standard multiplexing methods. METHODS We genotyped 326 frequently medicated individuals of European descent in Vanderbilt's biorepository linked to de-identified electronic medical records, BioVU, on the ADME Core Panel to assess quality and performance of the assay. We compared quality control metrics and determined the extent of direct and indirect marker overlap between the ADME Core Panel and the Illumina Omni1-Quad. RESULTS We found the quality of the ADME Core Panel data to be high, with exceptions in select copy number variants and markers in certain genes (notably CYP2D6). Most of the common variants on the ADME panel are genotyped by the Omni1, but absent rare variants and copy number variants could not be accurately tagged by single markers. CONCLUSION Our frequently medicated study population did not convincingly differ in allele frequency from reference populations, suggesting that heterogeneous clinical samples (with respect to medications) have similar allele frequency distributions in pharmacogenetics genes compared with reference populations.
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Affiliation(s)
- Matthew T Oetjens
- Center for Human Genetics Research & Department of Molecular Physiology & Biophysics, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, TN 37232-0700, USA
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12
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Oetjens M, Bush WS, Birdwell KA, Dilks HH, Bowton EA, Denny JC, Wilke RA, Roden DM, Crawford DC. Utilization of an EMR-biorepository to identify the genetic predictors of calcineurin-inhibitor toxicity in heart transplant recipients. Pac Symp Biocomput 2014:253-264. [PMID: 24297552 PMCID: PMC3923429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Calcineurin-inhibitors CI are immunosuppressive agents prescribed to patients after solid organ transplant to prevent rejection. Although these drugs have been transformative for allograft survival, long-term use is complicated by side effects including nephrotoxicity. Given the narrow therapeutic index of CI, therapeutic drug monitoring is used to prevent acute rejection from underdosing and acute toxicity from overdosing, but drug monitoring does not alleviate long-term side effects. Patients on calcineurin-inhibitors for long periods almost universally experience declines in renal function, and a subpopulation of transplant recipients ultimately develop chronic kidney disease that may progress to end stage renal disease attributable to calcineurin inhibitor toxicity (CNIT). Pharmacogenomics has the potential to identify patients who are at high risk for developing advanced chronic kidney disease caused by CNIT and providing them with existing alternate immunosuppressive therapy. In this study we utilized BioVU, Vanderbilt University Medical Center's DNA biorepository linked to de-identified electronic medical records to identify a cohort of 115 heart transplant recipients prescribed calcineurin-inhibitors to identify genetic risk factors for CNIT We identified 37 cases of nephrotoxicity in our cohort, defining nephrotoxicity as a monthly median estimated glomerular filtration rate (eGFR)<30 mL/min/1.73 m2 at least six months post-transplant for at least three consecutive months. All heart transplant patients were genotyped on the Illumina ADME Core Panel, a pharmacogenomic genotyping platform that assays 184 variants across 34 genes. In Cox regression analysis adjusting for age at transplant, pre-transplant chronic kidney disease, pre-transplant diabetes, and the three most significant principal components (PCAs), we did not identify any markers that met our multiple-testing threshold. As a secondary analysis we also modeled post-transplant eGFR directly with linear mixed models adjusted for age at transplant, cyclosporine use, median BMI, and the three most significant principal components. While no SNPs met our threshold for significance, a SNP previously identified in genetic studies of the dosing of tacrolimus CYP34A rs776746, replicated in an adjusted analysis at an uncorrected p-value of 0.02 (coeff(S.E.)=14.60(6.41)). While larger independent studies will be required to further validate this finding, this study underscores the EMRs usefulness as a resource for longitudinal pharmacogenetic study designs.
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Affiliation(s)
| | - William S. Bush
- Department of Biomedical Informatics, Center for Human Genetics Research
| | | | - Holli H. Dilks
- Vanderbilt Technologies for Advanced Genomics Core Facility
| | | | | | | | - Dan M. Roden
- Department of Medicine, Department of Pharmacology, Office of Personalized Medicine
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13
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Goodloe R, Brown-Gentry K, Gillani NB, Jin H, Mayo P, Allen M, McClellan B, Boston J, Sutcliffe C, Schnetz-Boutaud N, Dilks HH, Crawford DC. Lipid trait-associated genetic variation is associated with gallstone disease in the diverse Third National Health and Nutrition Examination Survey (NHANES III). BMC Med Genet 2013; 14:120. [PMID: 24256507 PMCID: PMC3870971 DOI: 10.1186/1471-2350-14-120] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2013] [Accepted: 10/22/2013] [Indexed: 01/10/2023]
Abstract
BACKGROUND Gallstone disease is one of the most common digestive disorders, affecting more than 30 million Americans. Previous twin studies suggest a heritability of 25% for gallstone formation. To date, one genome-wide association study (GWAS) has been performed in a population of European-descent. Several candidate gene studies have been performed in various populations, but most have been inconclusive. Given that gallstones consist of up to 80% cholesterol, we hypothesized that common genetic variants associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) would also be associated with gallstone risk. METHODS To test this hypothesis, the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study as part of the Population Architecture using Genomics and Epidemiology (PAGE) study performed tests of association between 49 GWAS-identified lipid trait SNPs and gallstone disease in non-Hispanic whites (446 cases and 1,962 controls), non-Hispanic blacks (179 cases and 1,540 controls), and Mexican Americans (227 cases and 1,478 controls) ascertained for the population-based Third National Health and Nutrition Examination Survey (NHANES III). RESULTS At a liberal significance threshold of 0.05, five, four, and four SNP(s) were associated with disease risk in non-Hispanic whites, non-Hispanic blacks, and Mexican Americans, respectively. No one SNP was associated with gallstone disease risk in all three racial/ethnic groups. The most significant association was observed for ABCG5 rs6756629 in non-Hispanic whites [odds ratio (OR) = 1.89; 95% confidence interval (CI) = 1.44-2.49; p = 0.0001). ABCG5 rs6756629 is in strong linkage disequilibrium with rs11887534 (D19H), a variant previously associated with gallstone disease risk in populations of European-descent. CONCLUSIONS We replicated a previously associated variant for gallstone disease risk in non-Hispanic whites. Further discovery and fine-mapping efforts in diverse populations are needed to fully describe the genetic architecture of gallstone disease risk in humans.
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Affiliation(s)
- Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Kristin Brown-Gentry
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Niloufar B Gillani
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Hailing Jin
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Ping Mayo
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Melissa Allen
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Bob McClellan
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Jonathan Boston
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Cara Sutcliffe
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Nathalie Schnetz-Boutaud
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
| | - Holli H Dilks
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA
| | - Dana C Crawford
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 519 Light Hall, Nashville, Tennessee 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA
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14
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Fesinmeyer MD, Meigs JB, North KE, Schumacher FR, Bůžková P, Franceschini N, Haessler J, Goodloe R, Spencer KL, Voruganti VS, Howard BV, Jackson R, Kolonel LN, Liu S, Manson JE, Monroe KR, Mukamal K, Dilks HH, Pendergrass SA, Nato A, Wan P, Wilkens LR, Le Marchand L, Ambite JL, Buyske S, Florez JC, Crawford DC, Hindorff LA, Haiman CA, Peters U, Pankow JS. Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study. BMC Med Genet 2013; 14:98. [PMID: 24063630 PMCID: PMC3849560 DOI: 10.1186/1471-2350-14-98] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/04/2012] [Accepted: 09/10/2013] [Indexed: 11/10/2022]
Abstract
BACKGROUND Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S. METHODS As part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites. RESULTS Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only. CONCLUSIONS Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.
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Affiliation(s)
- Megan D Fesinmeyer
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis MN, USA.
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15
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Dumitrescu L, Goodloe R, Brown-Gentry K, Mayo P, Allen M, Jin H, Gillani NB, Schnetz-Boutaud N, Dilks HH, Crawford DC. Serum vitamins A and E as modifiers of lipid trait genetics in the National Health and Nutrition Examination Surveys as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Hum Genet 2012; 131:1699-708. [PMID: 22688886 DOI: 10.1007/s00439-012-1186-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2011] [Accepted: 05/27/2012] [Indexed: 01/08/2023]
Abstract
Both environmental and genetic factors impact lipid traits. Environmental modifiers of known genotype-phenotype associations may account for some of the "missing heritability" of these traits. To identify such modifiers, we genotyped 23 lipid-associated variants identified previously through genome-wide association studies (GWAS) in 2,435 non-Hispanic white, 1,407 non-Hispanic black, and 1,734 Mexican-American samples collected for the National Health and Nutrition Examination Surveys (NHANES). Along with lipid levels, NHANES collected environmental variables, including fat-soluble macronutrient serum levels of vitamin A and E levels. As part of the Population Architecture using Genomics and Epidemiology (PAGE) study, we modeled gene-environment interactions between vitamin A or vitamin E and 23 variants previously associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. We identified three SNP × vitamin A and six SNP × vitamin E interactions at a significance threshold of p < 2.2 × 10(-3). The most significant interaction was APOB rs693 × vitamin E (p = 8.9 × 10(-7)) for LDL-C levels among Mexican-Americans. The nine significant interaction models individually explained 0.35-1.61% of the variation in any one of the lipid traits. Our results suggest that vitamins A and E may modify known genotype-phenotype associations; however, these interactions account for only a fraction of the overall variability observed for HDL-C, LDL-C, and TG levels in the general population.
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Affiliation(s)
- Logan Dumitrescu
- Center for Human Genetics Research, Vanderbilt University, 2215 Garland Avenue, 515B Light Hall, Nashville, TN 37232, USA.
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16
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Pulley JM, Denny JC, Peterson JF, Bernard GR, Vnencak-Jones CL, Ramirez AH, Delaney JT, Bowton E, Brothers K, Johnson K, Crawford DC, Schildcrout J, Masys DR, Dilks HH, Wilke RA, Clayton EW, Shultz E, Laposata M, McPherson J, Jirjis JN, Roden DM. Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project. Clin Pharmacol Ther 2012; 92:87-95. [PMID: 22588608 DOI: 10.1038/clpt.2011.371] [Citation(s) in RCA: 301] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The promise of "personalized medicine" guided by an understanding of each individual's genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision-support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health-care provider, identification of relevant genetic variations for implementation, assay reliability, point-of-care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point-of-care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.
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Affiliation(s)
- J M Pulley
- Department of Medical Administration, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
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17
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Guo XC, Scott K, Liu Y, Dean M, David V, Nelson GW, Johnson RC, Dilks HH, Lautenberger J, Kessing B, Martenson J, Guan L, Sun S, Deng H, Zheng Y, de The G, Liao J, Zeng Y, O'Brien SJ, Winkler CA. Genetic factors leading to chronic Epstein-Barr virus infection and nasopharyngeal carcinoma in South East China: study design, methods and feasibility. Hum Genomics 2006; 2:365-75. [PMID: 16848974 PMCID: PMC3525159 DOI: 10.1186/1479-7364-2-6-365] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Nasopharyngeal carcinoma (NPC) is a complex disease caused by a combination of Epstein-Barr virus chronic infection, the environment and host genes in a multi-step process of carcinogenesis. The identity of genetic factors involved in the development of chronic Epstein-Barr virus infection and NPC remains elusive, however. Here, we describe a two-phase, population-based, case-control study of Han Chinese from Guangxi province, where the NPC incidence rate rises to a high of 25-50 per 100,000 individuals. Phase I, powered to detect single gene associations, enrolled 984 subjects to determine feasibility, to develop infrastructure and logistics and to determine error rates in sample handling. A microsatellite screen of Phase I study participants, genotyped for 319 alleles from 34 microsatellites spanning an 18-megabase region of chromosome 4 (4p15.1-q12), previously implicated by a linkage analysis of familial NPC, found 14 alleles marginally associated with developing NPC or chronic immunoglobulin A production (p = 0.001-0.03). These associations lost significance after applying a correction for multiple tests. Although the present results await confirmation, the Phase II study population has tripled patient enrolment and has included environmental covariates, offering the potential to validate this and other genomic regions that influence the onset of NPC.
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Affiliation(s)
- Xiu Chan Guo
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
- Cangwu Institute for Nasopharyngeal Carcinoma Control and Prevention Wuzhou Guanxi China
| | - Kevin Scott
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Yan Liu
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Michael Dean
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Victor David
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - George W Nelson
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Randall C Johnson
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Holli H Dilks
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - James Lautenberger
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Bailey Kessing
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Janice Martenson
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Li Guan
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Shan Sun
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Hong Deng
- Cancer Institute of Wuzhou Wuzhou 543002, Guangxi China
| | - Yuming Zheng
- Cancer Institute of Wuzhou Wuzhou 543002, Guangxi China
| | | | - Jian Liao
- Cangwu Institute for Nasopharyngeal Carcinoma Control and Prevention Wuzhou Guanxi China
| | - Yi Zeng
- Institute for Viral Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China
| | - Stephen J O'Brien
- Laboratory of Genomic Diversity National Cancer Institute-Frederick Frederick MD 21702, USA
| | - Cheryl A Winkler
- Laboratory of Genomic Diversity SAIC Frederick National Cancer Institute-Frederick Frederick MD 21702, USA
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