Genetic Analysis Workshop 16 (GAW16) Problem 2 presented data from the Framingham Heart Study (FHS), an observational, prospective study of risk factors for cardiovascular disease begun in 1948. Data have been collected in three generations of family participants in the study and the data presented for GAW16 included phenotype data from all three generations, with four examinations of data collected repeatedly for the first two generations. The trait data consisted of information on blood pressure, hypertension treatment, lipid levels, diabetes and blood glucose, smoking, alcohol consumed, weight, and coronary heart disease incidence. Additionally, genotype data obtained through a genome-wide scan (FHS SHARe) of 550,000 single-nucleotide polymorphisms from Affymetrix chips were included with the GAW16 data. The genotype data were also used for GAW16 Problem 3, where simulated phenotypes were generated using the actual FHS genotypes. These data served to provide investigators with a rich resource to study the behavior of genome-wide scans with longitudinally collected family data and to develop and apply new procedures.National Heart, Lung and Blood Institute (2 N01-HC-25195-06); National Institutes of Health (National Institute of General Medical Sciences R01 GM031575

Atwood, Larry D.

Cupples, L. Adrienne

Heard-Costa, Nancy

Lee, Monica

BMC Proceedings

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Genetics Analysis Workshop 16 Problem 2: tTe Framingham Heart Study Data

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Boston UniversityOpenBU http://open.bu.eduFramingham Heart Study SPH Biostatistics Papers2009-12-15Genetics Analysis Workshop 16Problem 2: tTe Framingham HeartStudy DataCupples, L Adrienne, Nancy Heard-Costa, Monica Lee, Larry D Atwood. "GeneticsAnalysis Workshop 16 Problem 2: the Framingham Heart Study data" BMCProceedings 3(Suppl 7):S3. (2009)https://hdl.handle.net/2144/3083Boston UniversityBMC ProceedingsProceedingsGenetics Analysis Workshop 16 Problem 2:the Framingham Heart Study dataL Adrienne Cupples*1,2, Nancy Heard-Costa2,3, Monica Lee2,3,Larry D Atwood1,2,3 and the Framingham Heart Study InvestigatorsAddresses: 1Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston Massachusetts 02118,USA, 2Framingham Heart Study, 73 Mount Wayte Avenue, Framingham, Massachusetts 01702-5728, USA and 3Department of Neurology,Boston University School of Medicine, 75 East Newton Street, Boston Massachusetts 02118, USAE-mail: L Adrienne Cupples* - adrienne@bu.edu; Nancy Heard-Costa - nheard@bu.edu; Monica Lee - monny117@bu.edu;Larry D Atwood - lda@bu.edu*Corresponding authorfrom Genetic Analysis Workshop 16St Louis, MO, USA 17-20 September 2009Published: 15 December 2009BMC Proceedings 2009, 3(Suppl 7):S3 doi: 10.1186/1753-6561-3-S7-S3This article is available from: http://www.biomedcentral.com/1753-6561/3/S7/S3© 2009 Cupples et al; licensee BioMed Central Ltd.This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.AbstractGenetic Analysis Workshop 16 (GAW16) Problem 2 presented data from the Framingham HeartStudy (FHS), an observational, prospective study of risk factors for cardiovascular disease begun in1948. Data have been collected in three generations of family participants in the study and the datapresented for GAW16 included phenotype data from all three generations, with four examinationsof data collected repeatedly for the first two generations. The trait data consisted of information onblood pressure, hypertension treatment, lipid levels, diabetes and blood glucose, smoking, alcoholconsumed, weight, and coronary heart disease incidence. Additionally, genotype data obtainedthrough a genome-wide scan (FHS SHARe) of 550,000 single-nucleotide polymorphisms fromAffymetrix chips were included with the GAW16 data. The genotype data were also used forGAW16 Problem 3, where simulated phenotypes were generated using the actual FHS genotypes.These data served to provide investigators with a rich resource to study the behavior of genome-wide scans with longitudinally collected family data and to develop and apply new proceduresIntroductionThe Framingham Heart Study (FHS) – under thedirection of National Heart, Lung, and Blood Institute(NHLBI) – began in 1948 with the recruitment of adultsfrom the town of Framingham, Massachusetts. At thetime, little was known about the general causes of heartdisease and stroke, but death rates for cardiovasculardisease (CVD) had been increasing steadily since thebeginning of the 20th century and had become anAmerican epidemic. Even though rates of CVD havedeclined in recent decades, it remains the primary causeof death in both men and women in the US and in manyother parts of the world. The FHS is now conducted incollaboration with Boston University.Page 1 of 4(page number not for citation purposes)BioMed CentralOpen AccessThe objective of the FHS was to identify the commonfactors or characteristics that contribute to CVD byfollowing its development over a long period of time ina large group of population-based participants who hadnot yet developed overt symptoms of CVD or suffered aheart attack or stroke [1]. This project was unusuallyambitious. As one of the first population-based, epide-miologic studies, it planned to follow participantsprospectively for 20 years with repeat examinations.The NHLBI selected Framingham, Massachusetts becauseit was a moderate-sized town with a relatively stablepopulation that was thought to reflect many commu-nities in the US at that time. In the late 1940s an estimateof the number of residents in the age range 30-60 yearswho were eligible for recruitment was about 10,000individuals. The study aimed to recruit approximately6,000 participants. Between 1948 and 1953, theresearchers recruited 5,209 participants (2,336 menand 2,873 women) between the ages of 29 and 62 andbegan the first round of extensive physical examinationsand lifestyle interviews that they would later analyze forcommon patterns related to CVD development. Partici-pants were recruited from lists of addresses recorded forthe town census. Recruiters approached two out of everythree households for participation in the study. Whilethere was no intention to recruit families for familystudies, the plan was to recruit all household membersin the ages 30-60 within each house selected for study.Hence, the Study recruited many related individuals,including siblings, parent-child dyads, and 1,644 spousepairs. The investigators also thought that recruitment ofspouse pairs would encourage continued participationfor the original 20-year planned duration for the study.Since 1948, these participants have returned to the studyevery 2 years for a detailed medical history, physicalexamination, and laboratory tests. Now at more than 60years of follow up, there remain fewer than 500participants from this cohort, known as the OriginalCohort.Between 1971 and 1975 the Study enrolled a second-generation group – 5,124 of the original participants’children and the spouses of these children – toparticipate in similar examinations. An important goalin recruiting this Offspring Cohort was to evaluate theheritable factors involved in the development of CVDand its risk factors. Thus, the main strategy was to recruitoffspring where both parents participated in the OriginalCohort and those with one parent at higher risk of CVDdue to higher lipid levels. Of those recruited, 2,616participants are offspring of the original spouse pairs and34 are stepchildren. Another 898 offspring are childrenof cohort members where only one parent was a studyparticipant and 1,576 are spouses of the offspring. TheOffspring Cohort participants have returned every 4years through 2001 (except between Exams 1 and 2,which had an intervening 8 years) for follow-up exams,using protocols similar to those used for study of theOriginal Cohort.Between 2002 and 2005 the Study enrolled the thirdgeneration (Generation 3) into the FHS - 4,095 offspringof the second generation. None of their spouses wererecruited. At this time, the FHS also recruited anadditional 103 parents of this third generation whowere not recruited between 1971 and 1975. Data on thelatter group are not included in the GAW16 data. Withthe recruitment of this third generation, the Study hasincreasingly focused on genetic factors associated withthe development of CVD and its associated risk factors.The Generation 3 Cohort is now participating in itssecond examination. A description of the recruitment ofthis third generation and comparison with the earliergenerations at their initial recruitment is presented inSplansky et al. [2].We owe a great deal of gratitude to the Framinghamparticipants for this rich resource of data that has accruedover 60 years in three generations. It is their unflaggingcommitment to the Study that makes our researchpossible. Further information on the Study can befound at the Framingham Heart Study web site [3].Genotype dataIn-depth genetic studies did not begin in the FHS untilthe 1990s. In the late 1980s, family structures wereformally formed into extended pedigrees. Also in the late1980s and through the 1990s, investigators extractedDNA from blood samples of surviving FHS participants.Because many Original Cohort members had died bythis time, study investigators obtained DNA samplesfrom less than 30% of this cohort. In the mid-1990s intothe early 2000s, the NHLBI Mammalian GenotypingService, Center for Medical Genetics genotyped genome-wide microsatellites over several phases in the largest330 families in the Study. And in the early 2000s, a 100 kAffymetrix genome-wide scan was conducted in thesefamilies [4]. In 2007, the FHS entered a new phase withthe establishment of the FHS SHARe (SNP HealthAssociation Resource) project by NHLBI and BostonUniversity, for which Affymetrix performed dense SNPgenotyping using approximately 550,000 SNPs (Gene-Chip® Human Mapping 500 k Array Set and the 50 kHuman Gene Focused Panel) in 10,775 samples (someduplicates) from the three generations of participants(including over 900 pedigrees). The genotyping plat-forms for the FHS SHARe project were the 250 k Sty, the250 k Nsp, and the supplemental gene-centric 50 k chip.BMC Proceedings 2009, 3(Suppl 7):S3 http://www.biomedcentral.com/1753-6561/3/S7/S3Page 2 of 4(page number not for citation purposes)The Study obtained DNA for 89% of the participantsduring the 1990s. To maximize the power of the study,we also extracted DNA from 1,133 blood samples, drawnfrom participants who had no available DNA samples, toinclude in the SHARe project. These samples had beensitting in our freezers for some time, a few as far back asthe 1970s. We refer to these DNA samples as the legacysamples. These samples had a higher failure rate in thegenotyping process (40%) than the other 89% (3%). Asa result, to maximize the number of subjects included weused different criteria for a sample to succeed ingenotyping for these two types of DNA samples. Allnon-legacy samples must succeed on all three platforms,while legacy samples needed to pass on at least oneplatform. When a sample failed, additional attemptswere made. Samples that repeatedly failed two to fourtimes were called failures. Other samples failed due toissues of genotyped sex identification not matching ourrecords, low SNP concordance among SNPs commonacross arrays, or contamination. Eighty-nine percent ofthe legacy samples for which genotyping results areavailable passed all three platforms. The genotyping datafor the 10,043 samples from 9,354 participants thatpassed the Affymetrix criteria were additionally checkedfor sex consistency and consistency with family structure,resulting in genotyping data for 9,274 participants inFHS SHARe. Genotype calls were made with the BRLMMalgorithm.The National Center for Biotechnology Informationdatabase of Genotypes and Phenotypes [5] houses theSHARe database containing all ~550,000 SNPs andextensive phenotype data. This genome-wide denseSNP scan and a subset of phenotypes from the FHSwere the focus of the Genetic Analysis Workshop 16.These same genotypes were also used to simulate thephenotype data for GAW16 Problem 3 [6]. Recently, upto ~2.5 M imputed SNPs have been added to dbGaP, butthese genotypes were not available for the GAW16.Data for Genetic Analysis Workshop 16The FHS data sets for Genetic Analysis Workshop 16include pedigree, genotype, and phenotype data. Thephenotypic data provide information on those partici-pants who have consented to anyone’s use, includingthose at for-profit and not-for-profit institutions. Thepedigree file contains all biologically related participantsin the FHS and is not limited to the 7,230 participantswith full consent. A total of 7,130 participants havephenotype data: 373 Original Cohort, 2,760 OffspringCohort, and 3,997 Generation 3 participants. Nophenotypes were included from the 100 fully consentingnon-offspring spouses. Of the 7,230 consenting partici-pants, 6,979 are members of pedigrees and 251 areunrelated. Overall, there are a total of 6,848 participantswho are genotyped, including 6,621 in pedigrees and227 unrelated participants. There are 766 pedigrees with2 to 301 genotyped participants: 134 pedigrees with 2,123 with 3, 98 with 4, 85 with 5, 177 with 6 to 10,72 with 11 to 15, 30 with 16 to 20, and 47 with morethan 20.We selected data from a subset of examinations forGenetic Analysis Workshop 16: Exams 1 (1948-1953), 4(1954-1958), 7 (1960-1964), and 11 (1968-1971) forthe Original Cohort; Exams 1 (1971-1975), 3 (1983-1987), 5 (1991-1995), and 7 (1998-2001) for theOffspring Cohort; and Exam 1 for the Generation 3Cohort. We chose these exams so that data from FHSparticipants of approximately the same age from thethree cohorts were considered. Only one exam had beencompleted for Generation 3 and so only data from oneexam were available for these participants. Age, sex, anddescriptive statistics for these participants are provided inTable 1. Note that Original Cohort participants with dataincluded only the select few who survived ~40 years tohave DNA collected and to provide consent for theSHARe project.Genotype data sets contained ~550,000 genotypes foreach participant. We cleaned genotype data for familialrelationships. We evaluated whether the genotypes ofparticipants were consistent with their reported familialrelationships. We used PREST [7] and sib-kin from Aspex[8] to perform this analysis within families [9].Additionally, we checked for unknown (cryptic) first-degree relationships between families using PLINK[10,11]. In some cases, we altered familial relationshipsas a result. Such errors could occur from unknownfamilial relationships or sample mix-up. Cleaning at thisTable 1: Age and sex of Framingham Heart Study participantsfor GAW16 by cohort and examVariable OriginalCohortOffspringCohortGeneration3 CohortRecruited sample size 5209 5124 4095Number with 550 kgenotype data1529 3753 3893Sample size for GAW16 373 2760 3997Sample size for GAW16 withgenotypes357 2584 3811Ages (Mean ± SD)Exam 1 34.9 ± 3.9 33.7 ± 9.3 40.2 ± 8.8Exam 4 (Original),Exam 3 (Offspring)40.9 ± 3.9 46.3 ± 9.3 NAExam 7 (Original),Exam 5 (Offspring)47.0 ± 3.9 53.3 ± 9.2 NAExam 11 (Original),Exam 7 (Offspring)54.7 ± 3.8 60.2 ± 9.1 NA% Female, Exam 1 69.2% 54.4% 53.3%BMC Proceedings 2009, 3(Suppl 7):S3 http://www.biomedcentral.com/1753-6561/3/S7/S3Page 3 of 4(page number not for citation purposes)stage could result in all genotypes of some individualsbeing deleted. The genotype data set included legacyDNA samples, which were of poorer quality with ahigher rate of missing genotypes. Files with alleleintensities and confidence scores for each marker and .cel files were also available at dbGaP [5].The family structure file, defining the pedigree structures,was provided. This file also included indicators for whichcohort a participant belongs to and whether theparticipant is genotyped or phenotyped. There were8,732 participants in this file who have been genotyped.However, only data for those participants who consentedto general use (both for-profit and not-for-profit) wereavailable to GAW16.Participants with phenotype data who are not in thefamily file were not members of families and werebiologically unrelated to one another.Three phenotype files are provided: 1) Original Cohortparticipants, 2) Offspring Cohort participants, 3) Gen-eration 3 Cohort participants. These files provideinformation on demographics (sex and age), height,weight, traditional risk factors for coronary heart disease(blood pressure and hypertension, diabetes and bloodglucose, smoking, alcohol, and lipid levels), and onincident coronary heart disease and age at onset. Alsoincluded are age at onset of diabetes, age at death, andage at last contact. These participants were followed upfor events through 2006.List of abbreviations usedCVD: Cardiovascular disease; FHS: Framingham HeartStudy; GAW16: Genetic Analysis Workshop 16; NHLBI:National Heart, Lung, and Blood Institute.Competing interestsThe authors declare that they have no competinginterests.AcknowledgementsThis research was supported by NHLBI contract 2 N01-HC-25195-06.We, the authors of this manuscript, have put these phenotypic andgenotypic data together along with the family structures from the SHARedata for the Genetic Analysis Workshop 16. We are only a few of themany investigators within the Framingham Heart Study who have collectedand analyzed these data. We hereby salute those individuals who havecontributed an enormous amount of time and dedication to theFramingham Heart Study. More importantly, we acknowledge theinvaluable time, patience, and dedication of the participants in the Study,who have energetically come to clinic exams for so many years. It is theirresolute enthusiasm and commitment that have made the FraminghamHeart Study possible.The Genetic Analysis Workshops are supported by the NIH grant R01GM031575 from the National Institute of General Medical Sciences.This article has been published as part of BMC Proceedings Volume 3Supplement 7, 2009: Genetic Analysis Workshop 16. The full contents ofthe supplement are available online at http://www.biomedcentral.com/1753-6561/3?issue=S7.References1. Dawber T: The Framingham Study: The Epidemiology ofAtherosclerotic Disease.Cambridge, Massachusetts, HarvardUniversity Press; 1980.2. Splansky GL, Corey D, Yang Q, Atwood LD, Cupples LA,Benjamin EJ, D’Agostino RB Sr, Fox CS, Larson MG, Murabito JM,O’Donnell CJ, Vasan RS, Wolf PA and Levy D: The thirdgeneration cohort of the National Heart, Lung, and BloodInstitute’s Framingham Heart Study: design, recruitment,and initial examination. Am J Epidemiol 2007, 165:1328–1335.3. Framingham Heart Study. http://www.framinghamheartstudy.org/.4. Cupples LA, Arruda HT, Benjamin EJ, D’Agostino RB Sr, Demissie S,DeStefano AL, Dupuis J, Falls KM, Fox CS, Gottlieb DJ,Govindaraju DR, Guo CY, Heard-Costa NL, Hwang SJ,Kathiresan S, Kiel DP, Laramie JM, Larson MG, Levy D, Liu CY,Lunetta KL, Mailman MD, Manning AK, Meigs JB, Murabito JM,Newton-Cheh C, O’Connor GT, O’Donnell CJ, Pandey M,Seshadri S, Vasan RS, Wang ZY, Wilk JB, Wolf PA, Yang Q andAtwood LD: The Framingham Heart Study 100 K SNPgenome-wide association study resource: overview of 17phenotype working group reports. BMC Med Genet 2007,8(suppl 1):S1.5. dbGAP: Genotypes and Phenotypes. http://www.ncbi.nlm.nih.gov/sites/entrez?db=gap.6. Kraja AT, Culverhouse R, Daw EW, Wu J, Van Brunt A,Province MA and Borecki IB: The Genetic Analysis Workshop16 Problem 3: simulation of heritable longitudinal cardio-vascular phenotypes based on actual genome-wide single-nucleotide polymorphisms in the Framingham Heart Study.BMC Proc 2009, 3(suppl 7):S4.7. PREST documentation. http://galton.uchicago.edu/~mcpeek/soft-ware/prest/.8. The ASPEX package: affected sib-pair exclusion mapping.http://aspex.sourceforge.net/.9. McPeek MS and Sun L: Statistical tests for detection ofmisspecified relationships by use of genome-screen data.Am J Hum Genet 2000, 66:1076–1094.10. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA,Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ and Sham PC:PLINK: a tool set for whole-genome association andpopulation-based linkage analyses. Am J Hum Genet 2007,81:559–575.11. Plink...whole genome association analysis toolset. http://pngu.mgh.harvard.edu/~purcell/plink/.Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralBMC Proceedings 2009, 3(Suppl 7):S3 http://www.biomedcentral.com/1753-6561/3/S7/S3Page 4 of 4(page number not for citation purposes)

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Genetics Analysis Workshop 16 Problem 2: tTe Framingham Heart Study Data

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