8 results on '"Kovar Christie L"'
Search Results
2. ADAM19 and HTR4 Variants and Pulmonary Function.
- Author
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London, Stephanie J., Gao, Wei, Gharib, Sina A., Hancock, Dana B., Wilk, Jemma B., House, John S., Gibbs, Richard A., Muzny, Donna M., Lumley, Thomas, Franceschini, Nora, North, Kari E., Psaty, Bruce M., Kovar, Christie L., Coresh, Josef, Zhou, Yanhua, Heckbert, Susan R., Brody, Jennifer A., Morrison, Alanna C., and Dupuis, Josée
- Abstract
The pulmonary function measures of forced expiratory volume in 1 second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome-wide association studies (GWASs) have identified numerous loci associated with FEV1 and FEV1/FVC, but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWASs may explain the significant associations between FEV1/FVC and 2 genes: ADAM19 and HTR4.We sequenced ADAM19 and its promoter region along with the ≈21-kb portion of HTR4 harboring GWAS single-nucleotide polymorphisms for pulmonary function and analyzed associations with FEV1/FVC among 3983 participants of European ancestry from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Meta-analysis of common variants in each region identified statistically significant associations (316 tests; P<1.58×10
-4 ) with FEV1/FVC for 14 ADAM19 single-nucleotide polymorphisms and 24 HTR4 single-nucleotide polymorphisms. After conditioning on the sentinel GWASs hit in each gene (ADAM19 rs1422795, minor allele frequency=0.33 and HTR4 rs11168048, minor allele frequency=0.40], 1 single-nucleotide polymorphism remained statistically significant (ADAM19 rs13155908, minor allele frequency=0.12; P=1.56×10-4 ). Analysis of rare variants (minor allele frequency <1%) using sequence kernel association test did not identify associations with either region.Sequencing identified 1 common variant associated with FEV1/FVC independent of the sentinel ADAM19 GWAS hit and supports the original HTR4 GWAS findings. Rare variants do not seem to underlie GWAS associations with pulmonary function for common variants in ADAM19 and HTR4. [ABSTRACT FROM AUTHOR]- Published
- 2014
- Full Text
- View/download PDF
3. Strategies to Design and Analyze Targeted Sequencing Data.
- Author
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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, and Chen, Han
- Abstract
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.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.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. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
4. Targeted sequencing in candidate genes for atrial fibrillation: The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study.
- Author
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Lin, Honghuang, Sinner, Moritz F., Brody, Jennifer A., Arking, Dan E., Lunetta, Kathryn L., Rienstra, Michiel, Lubitz, Steven A., Magnani, Jared W., Sotoodehnia, Nona, McKnight, Barbara, McManus, David D., Boerwinkle, Eric, Psaty, Bruce M., Rotter, Jerome I., Bis, Joshua C., Gibbs, Richard A., Muzny, Donna, Kovar, Christie L., Morrison, Alanna C., and Gupta, Mayetri
- Abstract
Background: Genome-wide association studies (GWAS) have identified common genetic variants that predispose to atrial fibrillation (AF). It is unclear whether rare and low-frequency variants in genes implicated by such GWAS confer additional risk of AF. Objective: To study the association of genetic variants with AF at GWAS top loci. Methods: In the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study, we selected and sequenced 77 target gene regions from GWAS loci of complex diseases or traits, including 4 genes hypothesized to be related to AF (PRRX1, CAV1, CAV2, and ZFHX3). Sequencing was performed in participants with (n = 948) and without (n = 3330) AF from the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Massachusetts General Hospital. Results: One common variant (rs11265611; P = 1.70 × 10
−6 ) intronic to IL6R (interleukin-6 receptor gene) was significantly associated with AF after Bonferroni correction (odds ratio 0.70; 95% confidence interval 0.58–0.85). The variant was not genotyped or imputed by prior GWAS, but it is in linkage disequilibrium (r2 = .69) with the single-nucleotide polymorphism, with the strongest association with AF so far at this locus (rs4845625). In the rare variant joint analysis, damaging variants within the PRRX1 region showed significant association with AF after Bonferroni correction (P = .01). Conclusions: We identified 1 common single-nucleotide polymorphism and 1 gene region that were significantly associated with AF. Future sequencing efforts with larger sample sizes and more comprehensive genome coverage are anticipated to identify additional AF-related variants. [Copyright &y& Elsevier]- Published
- 2014
- Full Text
- View/download PDF
5. ADAM19and HTR4Variants and Pulmonary Function
- Author
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London, Stephanie J., Gao, Wei, Gharib, Sina A., Hancock, Dana B., Wilk, Jemma B., House, John S., Gibbs, Richard A., Muzny, Donna M., Lumley, Thomas, Franceschini, Nora, North, Kari E., Psaty, Bruce M., Kovar, Christie L., Coresh, Josef, Zhou, Yanhua, Heckbert, Susan R., Brody, Jennifer A., Morrison, Alanna C., and Dupuis, Josée
- Abstract
The pulmonary function measures of forced expiratory volume in 1 second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome-wide association studies (GWASs) have identified numerous loci associated with FEV1 and FEV1FVC, but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWASs may explain the significant associations between FEV1FVC and 2 genes: ADAM19and HTR4.
- Published
- 2014
- Full Text
- View/download PDF
6. Strategies to Design and Analyze Targeted Sequencing Data
- Author
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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., and Boerwinkle, Eric
- Abstract
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.
- Published
- 2014
- Full Text
- View/download PDF
7. Author Correction: Comparative and demographic analysis of orang-utan genomes
- Author
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Locke, Devin P., Hillier, LaDeana W., Warren, Wesley C., Worley, Kim C., Nazareth, Lynne V., Muzny, Donna M., Yang, Shiaw-Pyng, Wang, Zhengyuan, Chinwalla, Asif T., Minx, Pat, Mitreva, Makedonka, Cook, Lisa, Delehaunty, Kim D., Fronick, Catrina, Schmidt, Heather, Fulton, Lucinda A., Fulton, Robert S., Nelson, Joanne O., Magrini, Vincent, Pohl, Craig, Graves, Tina A., Markovic, Chris, Cree, Andy, Dinh, Huyen H., Hume, Jennifer, Kovar, Christie L., Fowler, Gerald R., Lunter, Gerton, Meader, Stephen, Heger, Andreas, Ponting, Chris P., Marques-Bonet, Tomas, Alkan, Can, Chen, Lin, Cheng, Ze, Kidd, Jeffrey M., Eichler, Evan E., White, Simon, Searle, Stephen, Vilella, Albert J., Chen, Yuan, Flicek, Paul, Ma, Jian, Raney, Brian, Suh, Bernard, Burhans, Richard, Herrero, Javier, Haussler, David, Faria, Rui, Fernando, Olga, Darré, Fleur, Farré, Domènec, Gazave, Elodie, Oliva, Meritxell, Navarro, Arcadi, Roberto, Roberta, Capozzi, Oronzo, Archidiacono, Nicoletta, Della Valle, Giuliano, Purgato, Stefania, Rocchi, Mariano, Konkel, Miriam K., Walker, Jerilyn A., Ullmer, Brygg, Batzer, Mark A., Smit, Arian F. A., Hubley, Robert, Casola, Claudio, Schrider, Daniel R., Hahn, Matthew W., Quesada, Victor, Puente, Xose S., Ordoñez, Gonzalo R., López-Otín, Carlos, Vinar, Tomas, Brejova, Brona, Ratan, Aakrosh, Harris, Robert S., Miller, Webb, Kosiol, Carolin, Lawson, Heather A., Taliwal, Vikas, Martins, André L., Siepel, Adam, RoyChoudhury, Arindam, Ma, Xin, Degenhardt, Jeremiah, Bustamante, Carlos D., Gutenkunst, Ryan N., Mailund, Thomas, Dutheil, Julien Y., Hobolth, Asger, Schierup, Mikkel H., Ryder, Oliver A., Yoshinaga, Yuko, de Jong, Pieter J., Weinstock, George M., Rogers, Jeffrey, Mardis, Elaine R., Gibbs, Richard A., and Wilson, Richard K.
- Published
- 2022
- Full Text
- View/download PDF
8. Implementation of preemptive DNA sequence–based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study
- Author
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Wang, Liewei, Scherer, Steven E., Bielinski, Suzette J., Muzny, Donna M., Jones, Leila A., Black, John Logan, Moyer, Ann M., Giri, Jyothsna, Sharp, Richard R., Matey, Eric T., Wright, Jessica A., Oyen, Lance J., Nicholson, Wayne T., Wiepert, Mathieu, Sullard, Terri, Curry, Timothy B., Rohrer Vitek, Carolyn R., McAllister, Tammy M., St. Sauver, Jennifer L., Caraballo, Pedro J., Lazaridis, Konstantinos N., Venner, Eric, Qin, Xiang, Hu, Jianhong, Kovar, Christie L., Korchina, Viktoriya, Walker, Kimberly, Doddapaneni, HarshaVardhan, Wu, Tsung-Jung, Raj, Ritika, Denson, Shawn, Liu, Wen, Chandanavelli, Gauthami, Zhang, Lan, Wang, Qiaoyan, Kalra, Divya, Karow, Mary Beth, Harris, Kimberley J., Sicotte, Hugues, Peterson, Sandra E., Barthel, Amy E., Moore, Brenda E., Skierka, Jennifer M., Kluge, Michelle L., Kotzer, Katrina E., Kloke, Karen, Vander Pol, Jessica M., Marker, Heather, Sutton, Joseph A., Kekic, Adrijana, Ebenhoh, Ashley, Bierle, Dennis M., Schuh, Michael J., Grilli, Christopher, Erickson, Sara, Umbreit, Audrey, Ward, Leah, Crosby, Sheena, Nelson, Eric A., Levey, Sharon, Elliott, Michelle, Peters, Steve G., Pereira, Naveen, Frye, Mark, Shamoun, Fadi, Goetz, Matthew P., Kullo, Iftikhar J., Wermers, Robert, Anderson, Jan A., Formea, Christine M., El Melik, Razan M., Zeuli, John D., Herges, Joseph R., Krieger, Carrie A., Hoel, Robert W., Taraba, Jodi L., St. Thomas, Scott R., Absah, Imad, Bernard, Matthew E., Fink, Stephanie R., Gossard, Andrea, Grubbs, Pamela L., Jacobson, Therese M., Takahashi, Paul, Zehe, Sharon C., Buckles, Susan, Bumgardner, Michelle, Gallagher, Colette, Fee-Schroeder, Kelliann, Nicholas, Nichole R., Powers, Melody L., Ragab, Ahmed K., Richardson, Darcy M., Stai, Anthony, Wilson, Jaymi, Pacyna, Joel E., Olson, Janet E., Sutton, Erica J., Beck, Annika T., Horrow, Caroline, Kalari, Krishna R., Larson, Nicholas B., Liu, Hongfang, Wang, Liwei, Lopes, Guilherme S., Borah, Bijan J., Freimuth, Robert R., Zhu, Ye, Jacobson, Debra J., Hathcock, Matthew A., Armasu, Sebastian M., McGree, Michaela E., Jiang, Ruoxiang, Koep, Tyler H., Ross, Jason L., Hilden, Matt, Bosse, Kathleen, Ramey, Bronwyn, Searcy, Isabelle, Boerwinkle, Eric, Gibbs, Richard A., and Weinshilboum, Richard M.
- Abstract
The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping.
- Published
- 2022
- Full Text
- View/download PDF
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