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Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study

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Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. / Lin, Honghuang; Wang, Min; Brody, Jennifer A; Bis, Joshua C; Dupuis, Josée; Lumley, Thomas; McKnight, Barbara; Rice, Kenneth M; Sitlani, Colleen M; Reid, Jeffrey G; Bressler, Jan; Liu, Xiaoming; Davis, Brian C; Johnson, Andrew D; O'Donnell, Christopher J; Kovar, Christie L; Dinh, Huyen; Wu, Yuanqing; Newsham, Irene; Chen, Han; Broka, Andi; DeStefano, Anita L; Gupta, Mayetri; Lunetta, Kathryn L; Liu, Ching-Ti; White, Charles C; Xing, Chuanhua; Zhou, Yanhua; Benjamin, Emelia J; Schnabel, Renate B; Heckbert, Susan R; Psaty, Bruce M; Muzny, Donna M; Cupples, L Adrienne; Morrison, Alanna C; Boerwinkle, Eric.

In: CIRC-CARDIOVASC GENE, Vol. 7, No. 3, 06.2014, p. 335-343.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Lin, H, Wang, M, Brody, JA, Bis, JC, Dupuis, J, Lumley, T, McKnight, B, Rice, KM, Sitlani, CM, Reid, JG, Bressler, J, Liu, X, Davis, BC, Johnson, AD, O'Donnell, CJ, Kovar, CL, Dinh, H, Wu, Y, Newsham, I, Chen, H, Broka, A, DeStefano, AL, Gupta, M, Lunetta, KL, Liu, C-T, White, CC, Xing, C, Zhou, Y, Benjamin, EJ, Schnabel, RB, Heckbert, SR, Psaty, BM, Muzny, DM, Cupples, LA, Morrison, AC & Boerwinkle, E 2014, 'Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study', CIRC-CARDIOVASC GENE, vol. 7, no. 3, pp. 335-343. https://doi.org/10.1161/CIRCGENETICS.113.000350

APA

Lin, H., Wang, M., Brody, J. A., Bis, J. C., Dupuis, J., Lumley, T., McKnight, B., Rice, K. M., Sitlani, C. M., Reid, J. G., Bressler, J., Liu, X., Davis, B. C., Johnson, A. D., O'Donnell, C. J., Kovar, C. L., Dinh, H., Wu, Y., Newsham, I., ... Boerwinkle, E. (2014). Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. CIRC-CARDIOVASC GENE, 7(3), 335-343. https://doi.org/10.1161/CIRCGENETICS.113.000350

Vancouver

Lin H, Wang M, Brody JA, Bis JC, Dupuis J, Lumley T et al. Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. CIRC-CARDIOVASC GENE. 2014 Jun;7(3):335-343. https://doi.org/10.1161/CIRCGENETICS.113.000350

Bibtex

@article{75d5a129a4764297ace7ca137e5abf3b,
title = "Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study",
abstract = "BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with ≥1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.",
keywords = "Adult, Aged, Aged, 80 and over, Aging/genetics, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases/epidemiology, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Research Design, Sequence Analysis, DNA",
author = "Honghuang Lin and Min Wang and Brody, {Jennifer A} and Bis, {Joshua C} and Jos{\'e}e Dupuis and Thomas Lumley and Barbara McKnight and Rice, {Kenneth M} and Sitlani, {Colleen M} and Reid, {Jeffrey G} and Jan Bressler and Xiaoming Liu and Davis, {Brian C} and Johnson, {Andrew D} and O'Donnell, {Christopher J} and Kovar, {Christie L} and Huyen Dinh and Yuanqing Wu and Irene Newsham and Han Chen and Andi Broka and DeStefano, {Anita L} and Mayetri Gupta and Lunetta, {Kathryn L} and Ching-Ti Liu and White, {Charles C} and Chuanhua Xing and Yanhua Zhou and Benjamin, {Emelia J} and Schnabel, {Renate B} and Heckbert, {Susan R} and Psaty, {Bruce M} and Muzny, {Donna M} and Cupples, {L Adrienne} and Morrison, {Alanna C} and Eric Boerwinkle",
note = "{\textcopyright} 2014 American Heart Association, Inc.",
year = "2014",
month = jun,
doi = "10.1161/CIRCGENETICS.113.000350",
language = "English",
volume = "7",
pages = "335--343",
journal = "CIRC-CARDIOVASC GENE",
issn = "1942-325X",
publisher = "Lippincott Williams and Wilkins",
number = "3",

}

RIS

TY - JOUR

T1 - Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study

AU - Lin, Honghuang

AU - Wang, Min

AU - Brody, Jennifer A

AU - Bis, Joshua C

AU - Dupuis, Josée

AU - Lumley, Thomas

AU - McKnight, Barbara

AU - Rice, Kenneth M

AU - Sitlani, Colleen M

AU - Reid, Jeffrey G

AU - Bressler, Jan

AU - Liu, Xiaoming

AU - Davis, Brian C

AU - Johnson, Andrew D

AU - O'Donnell, Christopher J

AU - Kovar, Christie L

AU - Dinh, Huyen

AU - Wu, Yuanqing

AU - Newsham, Irene

AU - Chen, Han

AU - Broka, Andi

AU - DeStefano, Anita L

AU - Gupta, Mayetri

AU - Lunetta, Kathryn L

AU - Liu, Ching-Ti

AU - White, Charles C

AU - Xing, Chuanhua

AU - Zhou, Yanhua

AU - Benjamin, Emelia J

AU - Schnabel, Renate B

AU - Heckbert, Susan R

AU - Psaty, Bruce M

AU - Muzny, Donna M

AU - Cupples, L Adrienne

AU - Morrison, Alanna C

AU - Boerwinkle, Eric

N1 - © 2014 American Heart Association, Inc.

PY - 2014/6

Y1 - 2014/6

N2 - BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with ≥1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

AB - BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with ≥1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Aging/genetics

KW - Cohort Studies

KW - Female

KW - Genetic Variation

KW - Genome-Wide Association Study

KW - Genomics

KW - Heart Diseases/epidemiology

KW - Humans

KW - Male

KW - Middle Aged

KW - Polymorphism, Single Nucleotide

KW - Research Design

KW - Sequence Analysis, DNA

U2 - 10.1161/CIRCGENETICS.113.000350

DO - 10.1161/CIRCGENETICS.113.000350

M3 - SCORING: Journal article

C2 - 24951659

VL - 7

SP - 335

EP - 343

JO - CIRC-CARDIOVASC GENE

JF - CIRC-CARDIOVASC GENE

SN - 1942-325X

IS - 3

ER -