Author: "Rice, Kenneth M." / Database: Supplemental Index - Searchworks@Jio Institute Digital Library Search Results

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1. Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits

Author: Keaton, Jacob M., Kamali, Zoha, Xie, Tian, Vaez, Ahmad, Williams, Ariel, Goleva, Slavina B., Ani, Alireza, Evangelou, Evangelos, Hellwege, Jacklyn N., Yengo, Loic, Young, William J., Traylor, Matthew, Giri, Ayush, Zheng, Zhili, Zeng, Jian, Chasman, Daniel I., Morris, Andrew P., Caulfield, Mark J., Hwang, Shih-Jen, Kooner, Jaspal S., Conen, David, Attia, John R., Morrison, Alanna C., Loos, Ruth J. F., Kristiansson, Kati, Schmidt, Reinhold, Hicks, Andrew A., Pramstaller, Peter P., Nelson, Christopher P., Samani, Nilesh J., Risch, Lorenz, Gyllensten, Ulf, Melander, Olle, Riese, Harriette, Wilson, James F., Campbell, Harry, Rich, Stephen S., Psaty, Bruce M., Lu, Yingchang, Rotter, Jerome I., Guo, Xiuqing, Rice, Kenneth M., Vollenweider, Peter, Sundström, Johan, Langenberg, Claudia, Tobin, Martin D., Giedraitis, Vilmantas, Luan, Jian’an, Tuomilehto, Jaakko, Kutalik, Zoltan, Ripatti, Samuli, Salomaa, Veikko, Girotto, Giorgia, Trompet, Stella, Jukema, J. Wouter, van der Harst, Pim, Ridker, Paul M., Giulianini, Franco, Vitart, Veronique, Goel, Anuj, Watkins, Hugh, Harris, Sarah E., Deary, Ian J., van der Most, Peter J., Oldehinkel, Albertine J., Keavney, Bernard D., Hayward, Caroline, Campbell, Archie, Boehnke, Michael, Scott, Laura J., Boutin, Thibaud, Mamasoula, Chrysovalanto, Järvelin, Marjo-Riitta, Peters, Annette, Gieger, Christian, Lakatta, Edward G., Cucca, Francesco, Hui, Jennie, Knekt, Paul, Enroth, Stefan, De Borst, Martin H., Polašek, Ozren, Concas, Maria Pina, Catamo, Eulalia, Cocca, Massimiliano, Li-Gao, Ruifang, Hofer, Edith, Schmidt, Helena, Spedicati, Beatrice, Waldenberger, Melanie, Strachan, David P., Laan, Maris, Teumer, Alexander, Dörr, Marcus, Gudnason, Vilmundur, Cook, James P., Ruggiero, Daniela, Kolcic, Ivana, Boerwinkle, Eric, Traglia, Michela, Lehtimäki, Terho, Raitakari, Olli T., Johnson, Andrew D., Newton-Cheh, Christopher, Brown, Morris J., Dominiczak, Anna F., Sever, Peter J., Poulter, Neil, Chambers, John C., Elosua, Roberto, Siscovick, David, Esko, Tõnu, Metspalu, Andres, Strawbridge, Rona J., Laakso, Markku, Hamsten, Anders, Hottenga, Jouke-Jan, de Geus, Eco, Morris, Andrew D., Palmer, Colin N. A., Nolte, Ilja M., Milaneschi, Yuri, Marten, Jonathan, Wright, Alan, Zeggini, Eleftheria, Howson, Joanna M. M., O’Donnell, Christopher J., Spector, Tim, Nalls, Mike A., Simonsick, Eleanor M., Liu, Yongmei, van Duijn, Cornelia M., Butterworth, Adam S., Danesh, John N., Menni, Cristina, Wareham, Nicholas J., Khaw, Kay-Tee, Sun, Yan V., Wilson, Peter W. F., Cho, Kelly, Visscher, Peter M., Denny, Joshua C., Levy, Daniel, Edwards, Todd L., Munroe, Patricia B., Snieder, Harold, and Warren, Helen R.
Abstract: Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P< 5 × 10−8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n= 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5–18.2 mmHg, P= 2.22 × 10−126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54–9.70; P= 4.13 × 10−44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781–0.801) to 0.826 (95% CI, 0.817–0.836, ∆AUROC, 0.035, P= 1.98 × 10−34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.
Published: 2024
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2. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies

Author: Li, Xihao, Quick, Corbin, Zhou, Hufeng, Gaynor, Sheila M., Liu, Yaowu, Chen, Han, Selvaraj, Margaret Sunitha, Sun, Ryan, Dey, Rounak, Arnett, Donna K., Bielak, Lawrence F., Bis, Joshua C., Blangero, John, Boerwinkle, Eric, Bowden, Donald W., Brody, Jennifer A., Cade, Brian E., Correa, Adolfo, Cupples, L. Adrienne, Curran, Joanne E., de Vries, Paul S., Duggirala, Ravindranath, Freedman, Barry I., Göring, Harald H. H., Guo, Xiuqing, Haessler, Jeffrey, Kalyani, Rita R., Kooperberg, Charles, Kral, Brian G., Lange, Leslie A., Manichaikul, Ani, Martin, Lisa W., McGarvey, Stephen T., Mitchell, Braxton D., Montasser, May E., Morrison, Alanna C., Naseri, Take, O’Connell, Jeffrey R., Palmer, Nicholette D., Peyser, Patricia A., Psaty, Bruce M., Raffield, Laura M., Redline, Susan, Reiner, Alexander P., Reupena, Muagututi’a Sefuiva, Rice, Kenneth M., Rich, Stephen S., Sitlani, Colleen M., Smith, Jennifer A., Taylor, Kent D., Vasan, Ramachandran S., Willer, Cristen J., Wilson, James G., Yanek, Lisa R., Zhao, Wei, Rotter, Jerome I., Natarajan, Pradeep, Peloso, Gina M., Li, Zilin, and Lin, Xihong
Abstract: Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.
Published: 2023
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3. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies

Author: Li, Zilin, Li, Xihao, Zhou, Hufeng, Gaynor, Sheila M., Selvaraj, Margaret Sunitha, Arapoglou, Theodore, Quick, Corbin, Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K., Auer, Paul L., Bielak, Lawrence F., Bis, Joshua C., Blackwell, Thomas W., Blangero, John, Boerwinkle, Eric, Bowden, Donald W., Brody, Jennifer A., Cade, Brian E., Conomos, Matthew P., Correa, Adolfo, Cupples, L. Adrienne, Curran, Joanne E., de Vries, Paul S., Duggirala, Ravindranath, Franceschini, Nora, Freedman, Barry I., Göring, Harald H. H., Guo, Xiuqing, Kalyani, Rita R., Kooperberg, Charles, Kral, Brian G., Lange, Leslie A., Lin, Bridget M., Manichaikul, Ani, Manning, Alisa K., Martin, Lisa W., Mathias, Rasika A., Meigs, James B., Mitchell, Braxton D., Montasser, May E., Morrison, Alanna C., Naseri, Take, O’Connell, Jeffrey R., Palmer, Nicholette D., Peyser, Patricia A., Psaty, Bruce M., Raffield, Laura M., Redline, Susan, Reiner, Alexander P., Reupena, Muagututi’a Sefuiva, Rice, Kenneth M., Rich, Stephen S., Smith, Jennifer A., Taylor, Kent D., Taub, Margaret A., Vasan, Ramachandran S., Weeks, Daniel E., Wilson, James G., Yanek, Lisa R., Zhao, Wei, Rotter, Jerome I., Willer, Cristen J., Natarajan, Pradeep, Peloso, Gina M., and Lin, Xihong
Abstract: Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.
Published: 2022
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4. Monogenic and Polygenic Contributions to QTc Prolongation in the Population

Author: Nauffal, Victor, Morrill, Valerie N., Jurgens, Sean J., Choi, Seung Hoan, Hall, Amelia W., Weng, Lu-Chen, Halford, Jennifer L., Austin-Tse, Christina, Haggerty, Christopher M., Harris, Stephanie L., Wong, Eugene K., Alonso, Alvaro, Arking, Dan E., Benjamin, Emelia J., Boerwinkle, Eric, Min, Yuan-I, Correa, Adolfo, Fornwalt, Brandon K., Heckbert, Susan R., Kooperberg, Charles, Lin, Henry J., J.F. Loos, Ruth, Rice, Kenneth M., Gupta, Namrata, Blackwell, Thomas W., Mitchell, Braxton D., Morrison, Alanna C., Psaty, Bruce M., Post, Wendy S., Redline, Susan, Rehm, Heidi L., Rich, Stephen S., Rotter, Jerome I., Soliman, Elsayed Z., Sotoodehnia, Nona, Lunetta, Kathryn L., Ellinor, Patrick T., and Lubitz, Steven A.
Published: 2022
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5. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Author: Gorski, Mathias, Jung, Bettina, Li, Yong, Matias-Garcia, Pamela R., Wuttke, Matthias, Coassin, Stefan, Thio, Chris H.L., Kleber, Marcus E., Winkler, Thomas W., Wanner, Veronika, Chai, Jin-Fang, Chu, Audrey Y., Cocca, Massimiliano, Feitosa, Mary F., Ghasemi, Sahar, Hoppmann, Anselm, Horn, Katrin, Li, Man, Nutile, Teresa, Scholz, Markus, Sieber, Karsten B., Teumer, Alexander, Tin, Adrienne, Wang, Judy, Tayo, Bamidele O., Ahluwalia, Tarunveer S., Almgren, Peter, Bakker, Stephan J.L., Banas, Bernhard, Bansal, Nisha, Biggs, Mary L., Boerwinkle, Eric, Bottinger, Erwin P., Brenner, Hermann, Carroll, Robert J., Chalmers, John, Chee, Miao-Li, Chee, Miao-Ling, Cheng, Ching-Yu, Coresh, Josef, de Borst, Martin H., Degenhardt, Frauke, Eckardt, Kai-Uwe, Endlich, Karlhans, Franke, Andre, Freitag-Wolf, Sandra, Gampawar, Piyush, Gansevoort, Ron T., Ghanbari, Mohsen, Gieger, Christian, Hamet, Pavel, Ho, Kevin, Hofer, Edith, Holleczek, Bernd, Xian Foo, Valencia Hui, Hutri-Kähönen, Nina, Hwang, Shih-Jen, Ikram, M. Arfan, Josyula, Navya Shilpa, Kähönen, Mika, Khor, Chiea-Chuen, Koenig, Wolfgang, Kramer, Holly, Krämer, Bernhard K., Kühnel, Brigitte, Lange, Leslie A., Lehtimäki, Terho, Lieb, Wolfgang, Alizadeh, Behrooz Z., Boezen, H. Marike, Franke, Lude, van der Harst, Pim, Navis, Gerjan, Rots, Marianne, Snieder, Harold, Swertz, Morris, Wolffenbuttel, Bruce H.R., Wijmenga, Cisca, Abecasis, Goncalo, Baras, Aris, Cantor, Michael, Coppola, Giovanni, Economides, Aris, Lotta, Luca A., Overton, John D., Reid, Jeffrey G., Shuldiner, Alan, Beechert, Christina, Forsythe, Caitlin, Fuller, Erin D., Gu, Zhenhua, Lattari, Michael, Lopez, Alexander, Overton, John D., Schleicher, Thomas D., Padilla, Maria Sotiropoulos, Toledo, Karina, Widom, Louis, Wolf, Sarah E., Pradhan, Manasi, Manoochehri, Kia, Ulloa, Ricardo H., Bai, Xiaodong, Balasubramanian, Suganthi, Barnard, Leland, Blumenfeld, Andrew, Eom, Gisu, Habegger, Lukas, Hawes, Alicia, Khalid, Shareef, Reid, Jeffrey G., Maxwell, Evan K., Salerno, William, Staples, Jeffrey C., Jones, Marcus B., Mitnaul, Lyndon J., Loos, Ruth J.F., Lukas, Mary Ann, Lyytikäinen, Leo-Pekka, Meisinger, Christa, Meitinger, Thomas, Melander, Olle, Milaneschi, Yuri, Mishra, Pashupati P., Mononen, Nina, Mychaleckyj, Josyf C., Nadkarni, Girish N., Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, Ilja M., O’Donoghue, Michelle L., Orho-Melander, Marju, Pendergrass, Sarah A., Penninx, Brenda W.J.H., Preuss, Michael H., Psaty, Bruce M., Raffield, Laura M., Raitakari, Olli T., Rettig, Rainer, Rheinberger, Myriam, Rice, Kenneth M., Rosenkranz, Alexander R., Rossing, Peter, Rotter, Jerome I., Sabanayagam, Charumathi, Schmidt, Helena, Schmidt, Reinhold, Schöttker, Ben, Schulz, Christina-Alexandra, Sedaghat, Sanaz, Shaffer, Christian M., Strauch, Konstantin, Szymczak, Silke, Taylor, Kent D., Tremblay, Johanne, Chaker, Layal, van der Harst, Pim, van der Most, Peter J., Verweij, Niek, Völker, Uwe, Waldenberger, Melanie, Wallentin, Lars, Waterworth, Dawn M., White, Harvey D., Wilson, James G., Wong, Tien-Yin, Woodward, Mark, Yang, Qiong, Yasuda, Masayuki, Yerges-Armstrong, Laura M., Zhang, Yan, Snieder, Harold, Wanner, Christoph, Böger, Carsten A., Köttgen, Anna, Kronenberg, Florian, Pattaro, Cristian, and Heid, Iris M.
Abstract: Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more (“Rapid3”; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2at follow-up among those with eGFRcrea 60 mL/min/1.73m2or more at baseline (“CKDi25”; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT(2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATMor LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.
Published: 2021
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6. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author: Taliun, Daniel, Harris, Daniel N., Kessler, Michael D., Carlson, Jedidiah, Szpiech, Zachary A., Torres, Raul, Taliun, Sarah A. Gagliano, Corvelo, André, Gogarten, Stephanie M., Kang, Hyun Min, Pitsillides, Achilleas N., LeFaive, Jonathon, Lee, Seung-been, Tian, Xiaowen, Browning, Brian L., Das, Sayantan, Emde, Anne-Katrin, Clarke, Wayne E., Loesch, Douglas P., Shetty, Amol C., Blackwell, Thomas W., Smith, Albert V., Wong, Quenna, Liu, Xiaoming, Conomos, Matthew P., Bobo, Dean M., Aguet, François, Albert, Christine, Alonso, Alvaro, Ardlie, Kristin G., Arking, Dan E., Aslibekyan, Stella, Auer, Paul L., Barnard, John, Barr, R. Graham, Barwick, Lucas, Becker, Lewis C., Beer, Rebecca L., Benjamin, Emelia J., Bielak, Lawrence F., Blangero, John, Boehnke, Michael, Bowden, Donald W., Brody, Jennifer A., Burchard, Esteban G., Cade, Brian E., Casella, James F., Chalazan, Brandon, Chasman, Daniel I., Chen, Yii-Der Ida, Cho, Michael H., Choi, Seung Hoan, Chung, Mina K., Clish, Clary B., Correa, Adolfo, Curran, Joanne E., Custer, Brian, Darbar, Dawood, Daya, Michelle, de Andrade, Mariza, DeMeo, Dawn L., Dutcher, Susan K., Ellinor, Patrick T., Emery, Leslie S., Eng, Celeste, Fatkin, Diane, Fingerlin, Tasha, Forer, Lukas, Fornage, Myriam, Franceschini, Nora, Fuchsberger, Christian, Fullerton, Stephanie M., Germer, Soren, Gladwin, Mark T., Gottlieb, Daniel J., Guo, Xiuqing, Hall, Michael E., He, Jiang, Heard-Costa, Nancy L., Heckbert, Susan R., Irvin, Marguerite R., Johnsen, Jill M., Johnson, Andrew D., Kaplan, Robert, Kardia, Sharon L. R., Kelly, Tanika, Kelly, Shannon, Kenny, Eimear E., Kiel, Douglas P., Klemmer, Robert, Konkle, Barbara A., Kooperberg, Charles, Köttgen, Anna, Lange, Leslie A., Lasky-Su, Jessica, Levy, Daniel, Lin, Xihong, Lin, Keng-Han, Liu, Chunyu, Loos, Ruth J. F., Garman, Lori, Gerszten, Robert, Lubitz, Steven A., Lunetta, Kathryn L., Mak, Angel C. Y., Manichaikul, Ani, Manning, Alisa K., Mathias, Rasika A., McManus, David D., McGarvey, Stephen T., Meigs, James B., Meyers, Deborah A., Mikulla, Julie L., Minear, Mollie A., Mitchell, Braxton D., Mohanty, Sanghamitra, Montasser, May E., Montgomery, Courtney, Morrison, Alanna C., Murabito, Joanne M., Natale, Andrea, Natarajan, Pradeep, Nelson, Sarah C., North, Kari E., O’Connell, Jeffrey R., Palmer, Nicholette D., Pankratz, Nathan, Peloso, Gina M., Peyser, Patricia A., Pleiness, Jacob, Post, Wendy S., Psaty, Bruce M., Rao, D. C., Redline, Susan, Reiner, Alexander P., Roden, Dan, Rotter, Jerome I., Ruczinski, Ingo, Sarnowski, Chloé, Schoenherr, Sebastian, Schwartz, David A., Seo, Jeong-Sun, Seshadri, Sudha, Sheehan, Vivien A., Sheu, Wayne H., Shoemaker, M. Benjamin, Smith, Nicholas L., Smith, Jennifer A., Sotoodehnia, Nona, Stilp, Adrienne M., Tang, Weihong, Taylor, Kent D., Telen, Marilyn, Thornton, Timothy A., Tracy, Russell P., Van Den Berg, David J., Vasan, Ramachandran S., Viaud-Martinez, Karine A., Vrieze, Scott, Weeks, Daniel E., Weir, Bruce S., Weiss, Scott T., Weng, Lu-Chen, Willer, Cristen J., Zhang, Yingze, Zhao, Xutong, Arnett, Donna K., Ashley-Koch, Allison E., Barnes, Kathleen C., Boerwinkle, Eric, Gabriel, Stacey, Gibbs, Richard, Rice, Kenneth M., Rich, Stephen S., Silverman, Edwin K., Qasba, Pankaj, Gan, Weiniu, Papanicolaou, George J., Nickerson, Deborah A., Browning, Sharon R., Zody, Michael C., Zöllner, Sebastian, Wilson, James G., Cupples, L. Adrienne, Laurie, Cathy C., Jaquish, Cashell E., Hernandez, Ryan D., O’Connor, Timothy D., and Abecasis, Gonçalo R.
Abstract: The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
Published: 2021
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7. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Author: Li, Xihao, Li, Zilin, Zhou, Hufeng, Gaynor, Sheila M., Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K., Aslibekyan, Stella, Ballantyne, Christie M., Bielak, Lawrence F., Blangero, John, Boerwinkle, Eric, Bowden, Donald W., Broome, Jai G., Conomos, Matthew P., Correa, Adolfo, Cupples, L. Adrienne, Curran, Joanne E., Freedman, Barry I., Guo, Xiuqing, Hindy, George, Irvin, Marguerite R., Kardia, Sharon L. R., Kathiresan, Sekar, Khan, Alyna T., Kooperberg, Charles L., Laurie, Cathy C., Liu, X. Shirley, Mahaney, Michael C., Manichaikul, Ani W., Martin, Lisa W., Mathias, Rasika A., McGarvey, Stephen T., Mitchell, Braxton D., Montasser, May E., Moore, Jill E., Morrison, Alanna C., O’Connell, Jeffrey R., Palmer, Nicholette D., Pampana, Akhil, Peralta, Juan M., Peyser, Patricia A., Psaty, Bruce M., Redline, Susan, Rice, Kenneth M., Rich, Stephen S., Smith, Jennifer A., Tiwari, Hemant K., Tsai, Michael Y., Vasan, Ramachandran S., Wang, Fei Fei, Weeks, Daniel E., Weng, Zhiping, Wilson, James G., Yanek, Lisa R., Neale, Benjamin M., Sunyaev, Shamil R., Abecasis, Gonçalo R., Rotter, Jerome I., Willer, Cristen J., Peloso, Gina M., Natarajan, Pradeep, and Lin, Xihong
Abstract: Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1and an intergenic region near APOC1P1associated with low-density lipoprotein cholesterol.
Published: 2020
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8. Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels

Author: Tin, Adrienne, Marten, Jonathan, Halperin Kuhns, Victoria L., Li, Yong, Wuttke, Matthias, Kirsten, Holger, Sieber, Karsten B., Qiu, Chengxiang, Gorski, Mathias, Yu, Zhi, Giri, Ayush, Sveinbjornsson, Gardar, Li, Man, Chu, Audrey Y., Hoppmann, Anselm, O’Connor, Luke J., Prins, Bram, Nutile, Teresa, Noce, Damia, Akiyama, Masato, Cocca, Massimiliano, Ghasemi, Sahar, van der Most, Peter J., Horn, Katrin, Xu, Yizhe, Fuchsberger, Christian, Sedaghat, Sanaz, Afaq, Saima, Amin, Najaf, Ärnlöv, Johan, Bakker, Stephan J. L., Bansal, Nisha, Baptista, Daniela, Bergmann, Sven, Biggs, Mary L., Biino, Ginevra, Boerwinkle, Eric, Bottinger, Erwin P., Boutin, Thibaud S., Brumat, Marco, Burkhardt, Ralph, Campana, Eric, Campbell, Archie, Campbell, Harry, Carroll, Robert J., Catamo, Eulalia, Chambers, John C., Ciullo, Marina, Concas, Maria Pina, Coresh, Josef, Corre, Tanguy, Cusi, Daniele, Felicita, Sala Cinzia, de Borst, Martin H., De Grandi, Alessandro, de Mutsert, Renée, de Vries, Aiko P. J., Delgado, Graciela, Demirkan, Ayşe, Devuyst, Olivier, Dittrich, Katalin, Eckardt, Kai-Uwe, Ehret, Georg, Endlich, Karlhans, Evans, Michele K., Gansevoort, Ron T., Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Gögele, Martin, Gordon, Scott D., Gudbjartsson, Daniel F., Gudnason, Vilmundur, Haller, Toomas, Hamet, Pavel, Harris, Tamara B., Hayward, Caroline, Hicks, Andrew A., Hofer, Edith, Holm, Hilma, Huang, Wei, Hutri-Kähönen, Nina, Hwang, Shih-Jen, Ikram, M. Arfan, Lewis, Raychel M., Ingelsson, Erik, Jakobsdottir, Johanna, Jonsdottir, Ingileif, Jonsson, Helgi, Joshi, Peter K., Josyula, Navya Shilpa, Jung, Bettina, Kähönen, Mika, Kamatani, Yoichiro, Kanai, Masahiro, Kerr, Shona M., Kiess, Wieland, Kleber, Marcus E., Koenig, Wolfgang, Kooner, Jaspal S., Körner, Antje, Kovacs, Peter, Krämer, Bernhard K., Kronenberg, Florian, Kubo, Michiaki, Kühnel, Brigitte, La Bianca, Martina, Lange, Leslie A., Lehne, Benjamin, Lehtimäki, Terho, Liu, Jun, Loeffler, Markus, Loos, Ruth J. F., Lyytikäinen, Leo-Pekka, Magi, Reedik, Mahajan, Anubha, Martin, Nicholas G., März, Winfried, Mascalzoni, Deborah, Matsuda, Koichi, Meisinger, Christa, Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, O’Donnell, Christopher J., Wilson, Otis D., Gaziano, J. Michael, Mishra, Pashupati P., Mohlke, Karen L., Mononen, Nina, Montgomery, Grant W., Mook-Kanamori, Dennis O., Müller-Nurasyid, Martina, Nadkarni, Girish N., Nalls, Mike A., Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, Ilja M., Noordam, Raymond, O’Connell, Jeffrey R., Olafsson, Isleifur, Padmanabhan, Sandosh, Penninx, Brenda W. J. H., Perls, Thomas, Peters, Annette, Pirastu, Mario, Pirastu, Nicola, Pistis, Giorgio, Polasek, Ozren, Ponte, Belen, Porteous, David J., Poulain, Tanja, Preuss, Michael H., Rabelink, Ton J., Raffield, Laura M., Raitakari, Olli T., Rettig, Rainer, Rheinberger, Myriam, Rice, Kenneth M., Rizzi, Federica, Robino, Antonietta, Rudan, Igor, Krajcoviechova, Alena, Cifkova, Renata, Rueedi, Rico, Ruggiero, Daniela, Ryan, Kathleen A., Saba, Yasaman, Salvi, Erika, Schmidt, Helena, Schmidt, Reinhold, Shaffer, Christian M., Smith, Albert V., Smith, Blair H., Spracklen, Cassandra N., Strauch, Konstantin, Stumvoll, Michael, Sulem, Patrick, Tajuddin, Salman M., Teren, Andrej, Thiery, Joachim, Thio, Chris H. L., Thorsteinsdottir, Unnur, Toniolo, Daniela, Tönjes, Anke, Tremblay, Johanne, Uitterlinden, André G., Vaccargiu, Simona, van der Harst, Pim, van Duijn, Cornelia M., Verweij, Niek, Völker, Uwe, Vollenweider, Peter, Waeber, Gerard, Waldenberger, Melanie, Whitfield, John B., Wild, Sarah H., Wilson, James F., Yang, Qiong, Zhang, Weihua, Zonderman, Alan B., Bochud, Murielle, Wilson, James G., Pendergrass, Sarah A., Ho, Kevin, Parsa, Afshin, Pramstaller, Peter P., Psaty, Bruce M., Böger, Carsten A., Snieder, Harold, Butterworth, Adam S., Okada, Yukinori, Edwards, Todd L., Stefansson, Kari, Susztak, Katalin, Scholz, Markus, Heid, Iris M., Hung, Adriana M., Teumer, Alexander, Pattaro, Cristian, Woodward, Owen M., Vitart, Veronique, and Köttgen, Anna
Abstract: Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1Aand HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.
Published: 2019
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9. A catalog of genetic loci associated with kidney function from analyses of a million individuals

Author: Wuttke, Matthias, Li, Yong, Li, Man, Sieber, Karsten B., Feitosa, Mary F., Gorski, Mathias, Tin, Adrienne, Wang, Lihua, Chu, Audrey Y., Hoppmann, Anselm, Kirsten, Holger, Giri, Ayush, Chai, Jin-Fang, Sveinbjornsson, Gardar, Tayo, Bamidele O., Nutile, Teresa, Fuchsberger, Christian, Marten, Jonathan, Cocca, Massimiliano, Ghasemi, Sahar, Xu, Yizhe, Horn, Katrin, Noce, Damia, van der Most, Peter J., Sedaghat, Sanaz, Yu, Zhi, Akiyama, Masato, Afaq, Saima, Ahluwalia, Tarunveer S., Almgren, Peter, Amin, Najaf, Ärnlöv, Johan, Bakker, Stephan J. L., Bansal, Nisha, Baptista, Daniela, Bergmann, Sven, Biggs, Mary L., Biino, Ginevra, Boehnke, Michael, Boerwinkle, Eric, Boissel, Mathilde, Bottinger, Erwin P., Boutin, Thibaud S., Brenner, Hermann, Brumat, Marco, Burkhardt, Ralph, Butterworth, Adam S., Campana, Eric, Campbell, Archie, Campbell, Harry, Canouil, Mickaël, Carroll, Robert J., Catamo, Eulalia, Chambers, John C., Chee, Miao-Ling, Chee, Miao-Li, Chen, Xu, Cheng, Ching-Yu, Cheng, Yurong, Christensen, Kaare, Cifkova, Renata, Ciullo, Marina, Concas, Maria Pina, Cook, James P., Coresh, Josef, Corre, Tanguy, Sala, Cinzia Felicita, Cusi, Daniele, Danesh, John, Daw, E. Warwick, de Borst, Martin H., De Grandi, Alessandro, de Mutsert, Renée, de Vries, Aiko P. J., Degenhardt, Frauke, Delgado, Graciela, Demirkan, Ayse, Di Angelantonio, Emanuele, Dittrich, Katalin, Divers, Jasmin, Dorajoo, Rajkumar, Eckardt, Kai-Uwe, Ehret, Georg, Elliott, Paul, Endlich, Karlhans, Evans, Michele K., Felix, Janine F., Foo, Valencia Hui Xian, Franco, Oscar H., Franke, Andre, Freedman, Barry I., Freitag-Wolf, Sandra, Friedlander, Yechiel, Froguel, Philippe, Gansevoort, Ron T., Gao, He, Gasparini, Paolo, Gaziano, J. Michael, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Giulianini, Franco, Gögele, Martin, Gordon, Scott D., Gudbjartsson, Daniel F., Gudnason, Vilmundur, Haller, Toomas, Hamet, Pavel, Harris, Tamara B., Hartman, Catharina A., Hayward, Caroline, Hellwege, Jacklyn N., Heng, Chew-Kiat, Hicks, Andrew A., Hofer, Edith, Huang, Wei, Hutri-Kähönen, Nina, Hwang, Shih-Jen, Ikram, M. Arfan, Indridason, Olafur S., Ingelsson, Erik, Ising, Marcus, Jaddoe, Vincent W. V., Jakobsdottir, Johanna, Jonas, Jost B., Joshi, Peter K., Josyula, Navya Shilpa, Jung, Bettina, Kähönen, Mika, Kamatani, Yoichiro, Kammerer, Candace M., Kanai, Masahiro, Kastarinen, Mika, Kerr, Shona M., Khor, Chiea-Chuen, Kiess, Wieland, Kleber, Marcus E., Koenig, Wolfgang, Kooner, Jaspal S., Körner, Antje, Kovacs, Peter, Kraja, Aldi T., Krajcoviechova, Alena, Kramer, Holly, Krämer, Bernhard K., Kronenberg, Florian, Kubo, Michiaki, Kühnel, Brigitte, Kuokkanen, Mikko, Kuusisto, Johanna, La Bianca, Martina, Laakso, Markku, Lange, Leslie A., Langefeld, Carl D., Lee, Jeannette Jen-Mai, Lehne, Benjamin, Lehtimäki, Terho, Lieb, Wolfgang, Lim, Su-Chi, Lind, Lars, Lindgren, Cecilia M., Liu, Jun, Liu, Jianjun, Loeffler, Markus, Loos, Ruth J. F., Lucae, Susanne, Lukas, Mary Ann, Lyytikäinen, Leo-Pekka, Mägi, Reedik, Magnusson, Patrik K. E., Mahajan, Anubha, Martin, Nicholas G., Martins, Jade, März, Winfried, Mascalzoni, Deborah, Matsuda, Koichi, Meisinger, Christa, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mikaelsdottir, Evgenia K., Milaneschi, Yuri, Miliku, Kozeta, Mishra, Pashupati P., Mohlke, Karen L., Mononen, Nina, Montgomery, Grant W., Mook-Kanamori, Dennis O., Mychaleckyj, Josyf C., Nadkarni, Girish N., Nalls, Mike A., Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, Ilja M., Noordam, Raymond, O’Connell, Jeffrey, O’Donoghue, Michelle L., Olafsson, Isleifur, Oldehinkel, Albertine J., Orho-Melander, Marju, Ouwehand, Willem H., Padmanabhan, Sandosh, Palmer, Nicholette D., Palsson, Runolfur, Penninx, Brenda W. J. H., Perls, Thomas, Perola, Markus, Pirastu, Mario, Pirastu, Nicola, Pistis, Giorgio, Podgornaia, Anna I., Polasek, Ozren, Ponte, Belen, Porteous, David J., Poulain, Tanja, Pramstaller, Peter P., Preuss, Michael H., Prins, Bram P., Province, Michael A., Rabelink, Ton J., Raffield, Laura M., Raitakari, Olli T., Reilly, Dermot F., Rettig, Rainer, Rheinberger, Myriam, Rice, Kenneth M., Ridker, Paul M., Rivadeneira, Fernando, Rizzi, Federica, Roberts, David J., Robino, Antonietta, Rossing, Peter, Rudan, Igor, Rueedi, Rico, Ruggiero, Daniela, Ryan, Kathleen A., Saba, Yasaman, Sabanayagam, Charumathi, Salomaa, Veikko, Salvi, Erika, Saum, Kai-Uwe, Schmidt, Helena, Schmidt, Reinhold, Schöttker, Ben, Schulz, Christina-Alexandra, Schupf, Nicole, Shaffer, Christian M., Shi, Yuan, Smith, Albert V., Smith, Blair H., Soranzo, Nicole, Spracklen, Cassandra N., Strauch, Konstantin, Stringham, Heather M., Stumvoll, Michael, Svensson, Per O., Szymczak, Silke, Tai, E-Shyong, Tajuddin, Salman M., Tan, Nicholas Y. Q., Taylor, Kent D., Teren, Andrej, Tham, Yih-Chung, Thiery, Joachim, Thio, Chris H. L., Thomsen, Hauke, Thorleifsson, Gudmar, Toniolo, Daniela, Tönjes, Anke, Tremblay, Johanne, Tzoulaki, Ioanna, Uitterlinden, André G., Vaccargiu, Simona, van Dam, Rob M., van der Harst, Pim, van Duijn, Cornelia M., Velez Edward, Digna R., Verweij, Niek, Vogelezang, Suzanne, Völker, Uwe, Vollenweider, Peter, Waeber, Gerard, Waldenberger, Melanie, Wallentin, Lars, Wang, Ya Xing, Wang, Chaolong, Waterworth, Dawn M., Bin Wei, Wen, White, Harvey, Whitfield, John B., Wild, Sarah H., Wilson, James F., Wojczynski, Mary K., Wong, Charlene, Wong, Tien-Yin, Xu, Liang, Yang, Qiong, Yasuda, Masayuki, Yerges-Armstrong, Laura M., Zhang, Weihua, Zonderman, Alan B., Rotter, Jerome I., Bochud, Murielle, Psaty, Bruce M., Vitart, Veronique, Wilson, James G., Dehghan, Abbas, Parsa, Afshin, Chasman, Daniel I., Ho, Kevin, Morris, Andrew P., Devuyst, Olivier, Akilesh, Shreeram, Pendergrass, Sarah A., Sim, Xueling, Böger, Carsten A., Okada, Yukinori, Edwards, Todd L., Snieder, Harold, Stefansson, Kari, Hung, Adriana M., Heid, Iris M., Scholz, Markus, Teumer, Alexander, Köttgen, Anna, and Pattaro, Cristian
Abstract: Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n= 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n= 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
Published: 2019
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10. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38for White Matter Hyperintensities on Brain Magnetic Resonance Imaging

Author: Jian, Xueqiu, Satizabal, Claudia L., Smith, Albert V., Wittfeld, Katharina, Bis, Joshua C., Smith, Jennifer A., Hsu, Fang-Chi, Nho, Kwangsik, Hofer, Edith, Hagenaars, Saskia P., Nyquist, Paul A., Mishra, Aniket, Adams, Hieab H.H., Li, Shuo, Teumer, Alexander, Zhao, Wei, Freedman, Barry I., Saba, Yasaman, Yanek, Lisa R., Chauhan, Ganesh, van Buchem, Mark A., Cushman, Mary, Royle, Natalie A., Bryan, R. Nick, Niessen, Wiro J., Windham, Beverly G., DeStefano, Anita L., Habes, Mohamad, Heckbert, Susan R., Palmer, Nicholette D., Lewis, Cora E., Eiriksdottir, Gudny, Maillard, Pauline, Mathias, Rasika A., Homuth, Georg, Valdés-Hernández, Maria del C., Divers, Jasmin, Beiser, Alexa S., Langner, Sönke, Rice, Kenneth M., Bastin, Mark E., Yang, Qiong, Maldjian, Joseph A., Starr, John M., Sidney, Stephen, Risacher, Shannon L., Uitterlinden, André G., Gudnason, Vilmundur G., Nauck, Matthias, Rotter, Jerome I., Schreiner, Pamela J., Boerwinkle, Eric, van Duijn, Cornelia M., Mazoyer, Bernard, von Sarnowski, Bettina, Gottesman, Rebecca F., Levy, Daniel, Sigurdsson, Sigurdur, Vernooij, Meike W., Turner, Stephen T., Schmidt, Reinhold, Wardlaw, Joanna M., Psaty, Bruce M., Mosley, Thomas H., DeCarli, Charles S., Saykin, Andrew J., Bowden, Donald W., Becker, Diane M., Deary, Ian J., Schmidt, Helena, Kardia, Sharon L.R., Ikram, M. Arfan, Debette, Stéphanie, Grabe, Hans J., Longstreth, W.T., Seshadri, Sudha, Launer, Lenore J., and Fornage, Myriam
Abstract: Supplemental Digital Content is available in the text.
Published: 2018
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11. Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology

Author: Brody, Jennifer A, Morrison, Alanna C, Bis, Joshua C, O'Connell, Jeffrey R, Brown, Michael R, Huffman, Jennifer E, Ames, Darren C, Carroll, Andrew, Conomos, Matthew P, Gabriel, Stacey, Gibbs, Richard A, Gogarten, Stephanie M, Gupta, Namrata, Jaquish, Cashell E, Johnson, Andrew D, Lewis, Joshua P, Liu, Xiaoming, Manning, Alisa K, Papanicolaou, George J, Pitsillides, Achilleas N, Rice, Kenneth M, Salerno, William, Sitlani, Colleen M, Smith, Nicholas L, Heckbert, Susan R, Laurie, Cathy C, Mitchell, Braxton D, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Wilson, James G, Boerwinkle, Eric, Psaty, Bruce M, and Cupples, L Adrienne
Published: 2017
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12. A genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium

Author: Noordam, Raymond, Sitlani, Colleen M, Avery, Christy L, Stewart, James D, Gogarten, Stephanie M, Wiggins, Kerri L, Trompet, Stella, Warren, Helen R, Sun, Fangui, Evans, Daniel S, Li, Xiaohui, Li, Jin, Smith, Albert V, Bis, Joshua C, Brody, Jennifer A, Busch, Evan L, Caulfield, Mark J, Chen, Yii-Der I, Cummings, Steven R, Cupples, L Adrienne, Duan, Qing, Franco, Oscar H, Máéndez-Giráéáldez, Rául, Harris, Tamara B, Heckbert, Susan R, van Heemst, Diana, Hofman, Albert, Floyd, James S, Kors, Jan A, Launer, Lenore J, Li, Yun, Li-Gao, Ruifang, Lange, Leslie A, Lin, Henry J, de Mutsert, Renáéáée, Napier, Melanie D, Newton-Cheh, Christopher, Poulter, Neil, Reiner, Alexander P, Rice, Kenneth M, Roach, Jeffrey, Rodriguez, Carlos J, Rosendaal, Frits R, Sattar, Naveed, Sever, Peter, Seyerle, Amanda A, Slagboom, P Eline, Soliman, Elsayed Z, Sotoodehnia, Nona, Stott, David J, Sturmer, Til, Taylor, Kent D, Thornton, Timothy A, Uitterlinden, Andráéáéé G, Wilhelmsen, Kirk C, Wilson, James G, Gudnason, Vilmundur, Jukema, J Wouter, Laurie, Cathy C, Liu, Yongmei, Mook-Kanamori, Dennis O, Munroe, Patricia B, Rotter, Jerome I, Vasan, Ramachandran S, Psaty, Bruce M, Stricker, Bruno H, and Whitsel, Eric A
Abstract: BackgroundIncreased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals.Methods and resultsWe conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in BRE(β=56.3, pinteraction=3.9e−9) and rs9830388 in UBE2E2(β=25.2, pinteraction=1.7e−8). In Hispanic/Latino cohorts, rs2291477 in TGFBR3significantly modified the association between TCAs and QT intervals (β=9.3, pinteraction=2.55e−8). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (pinteraction>0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries.ConclusionsAmong Europeans, TCA interactions with variants in BREand UBE2E2were identified in relation to RR intervals. Among Hispanic/Latinos, variants in TGFBR3modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.
Published: 2017
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13. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals

Author: Ehret, Georg B, Ferreira, Teresa, Chasman, Daniel I, Jackson, Anne U, Schmidt, Ellen M, Johnson, Toby, Thorleifsson, Gudmar, Luan, Jian'an, Donnelly, Louise A, Kanoni, Stavroula, Petersen, Ann-Kristin, Pihur, Vasyl, Strawbridge, Rona J, Shungin, Dmitry, Hughes, Maria F, Meirelles, Osorio, Kaakinen, Marika, Bouatia-Naji, Nabila, Kristiansson, Kati, Shah, Sonia, Kleber, Marcus E, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Fava, Cristiano, Eriksson, Niclas, Nolte, Ilja M, Magnusson, Patrik K, Salfati, Elias L, Rallidis, Loukianos S, Theusch, Elizabeth, Smith, Andrew J P, Folkersen, Lasse, Witkowska, Kate, Pers, Tune H, Joehanes, Roby, Kim, Stuart K, Lataniotis, Lazaros, Jansen, Rick, Johnson, Andrew D, Warren, Helen, Kim, Young Jin, Zhao, Wei, Wu, Ying, Tayo, Bamidele O, Bochud, Murielle, Absher, Devin, Adair, Linda S, Amin, Najaf, Arking, Dan E, Axelsson, Tomas, Baldassarre, Damiano, Balkau, Beverley, Bandinelli, Stefania, Barnes, Michael R, Barroso, Inês, Bevan, Stephen, Bis, Joshua C, Bjornsdottir, Gyda, Boehnke, Michael, Boerwinkle, Eric, Bonnycastle, Lori L, Boomsma, Dorret I, Bornstein, Stefan R, Brown, Morris J, Burnier, Michel, Cabrera, Claudia P, Chambers, John C, Chang, I-Shou, Cheng, Ching-Yu, Chines, Peter S, Chung, Ren-Hua, Collins, Francis S, Connell, John M, Döring, Angela, Dallongeville, Jean, Danesh, John, de Faire, Ulf, Delgado, Graciela, Dominiczak, Anna F, Doney, Alex S F, Drenos, Fotios, Edkins, Sarah, Eicher, John D, Elosua, Roberto, Enroth, Stefan, Erdmann, Jeanette, Eriksson, Per, Esko, Tonu, Evangelou, Evangelos, Evans, Alun, Fall, Tove, Farrall, Martin, Felix, Janine F, Ferrières, Jean, Ferrucci, Luigi, Fornage, Myriam, Forrester, Terrence, Franceschini, Nora, Franco, Oscar H, Franco-Cereceda, Anders, Fraser, Ross M, Ganesh, Santhi K, Gao, He, Gertow, Karl, Gianfagna, Francesco, Gigante, Bruna, Giulianini, Franco, Goel, Anuj, Goodall, Alison H, Goodarzi, Mark O, Gorski, Mathias, Gräßler, Jürgen, Groves, Christopher J, Gudnason, Vilmundur, Gyllensten, Ulf, Hallmans, Göran, Hartikainen, Anna-Liisa, Hassinen, Maija, Havulinna, Aki S, Hayward, Caroline, Hercberg, Serge, Herzig, Karl-Heinz, Hicks, Andrew A, Hingorani, Aroon D, Hirschhorn, Joel N, Hofman, Albert, Holmen, Jostein, Holmen, Oddgeir Lingaas, Hottenga, Jouke-Jan, Howard, Phil, Hsiung, Chao A, Hunt, Steven C, Ikram, M Arfan, Illig, Thomas, Iribarren, Carlos, Jensen, Richard A, Kähönen, Mika, Kang, Hyun Min, Kathiresan, Sekar, Keating, Brendan J, Khaw, Kay-Tee, Kim, Yun Kyoung, Kim, Eric, Kivimaki, Mika, Klopp, Norman, Kolovou, Genovefa, Komulainen, Pirjo, Kooner, Jaspal S, Kosova, Gulum, Krauss, Ronald M, Kuh, Diana, Kutalik, Zoltan, Kuusisto, Johanna, Kvaløy, Kirsti, Lakka, Timo A, Lee, Nanette R, Lee, I-Te, Lee, Wen-Jane, Levy, Daniel, Li, Xiaohui, Liang, Kae-Woei, Lin, Honghuang, Lin, Li, Lindström, Jaana, Lobbens, Stéphane, Männistö, Satu, Müller, Gabriele, Müller-Nurasyid, Martina, Mach, François, Markus, Hugh S, Marouli, Eirini, McCarthy, Mark I, McKenzie, Colin A, Meneton, Pierre, Menni, Cristina, Metspalu, Andres, Mijatovic, Vladan, Moilanen, Leena, Montasser, May E, Morris, Andrew D, Morrison, Alanna C, Mulas, Antonella, Nagaraja, Ramaiah, Narisu, Narisu, Nikus, Kjell, O'Donnell, Christopher J, O'Reilly, Paul F, Ong, Ken K, Paccaud, Fred, Palmer, Cameron D, Parsa, Afshin, Pedersen, Nancy L, Penninx, Brenda W, Perola, Markus, Peters, Annette, Poulter, Neil, Pramstaller, Peter P, Psaty, Bruce M, Quertermous, Thomas, Rao, Dabeeru C, Rasheed, Asif, Rayner, N William, Renström, Frida, Rettig, Rainer, Rice, Kenneth M, Roberts, Robert, Rose, Lynda M, Rossouw, Jacques, Samani, Nilesh J, Sanna, Serena, Saramies, Jouko, Schunkert, Heribert, Sebert, Sylvain, Sheu, Wayne H-H, Shin, Young-Ah, Sim, Xueling, Smit, Johannes H, Smith, Albert V, Sosa, Maria X, Spector, Tim D, Stančáková, Alena, Stanton, Alice V, Stirrups, Kathleen E, Stringham, Heather M, Sundstrom, Johan, Swift, Amy J, Syvänen, Ann-Christine, Tai, E-Shyong, Tanaka, Toshiko, Tarasov, Kirill V, Teumer, Alexander, Thorsteinsdottir, Unnur, Tobin, Martin D, Tremoli, Elena, Uitterlinden, Andre G, Uusitupa, Matti, Vaez, Ahmad, Vaidya, Dhananjay, van Duijn, Cornelia M, van Iperen, Erik P A, Vasan, Ramachandran S, Verwoert, Germaine C, Virtamo, Jarmo, Vitart, Veronique, Voight, Benjamin F, Vollenweider, Peter, Wagner, Aline, Wain, Louise V, Wareham, Nicholas J, Watkins, Hugh, Weder, Alan B, Westra, Harm-Jan, Wilks, Rainford, Wilsgaard, Tom, Wilson, James F, Wong, Tien Y, Yang, Tsun-Po, Yao, Jie, Yengo, Loic, Zhang, Weihua, Zhao, Jing Hua, Zhu, Xiaofeng, Bovet, Pascal, Cooper, Richard S, Mohlke, Karen L, Saleheen, Danish, Lee, Jong-Young, Elliott, Paul, Gierman, Hinco J, Willer, Cristen J, Franke, Lude, Hovingh, G Kees, Taylor, Kent D, Dedoussis, George, Sever, Peter, Wong, Andrew, Lind, Lars, Assimes, Themistocles L, Njølstad, Inger, Schwarz, Peter E H, Langenberg, Claudia, Snieder, Harold, Caulfield, Mark J, Melander, Olle, Laakso, Markku, Saltevo, Juha, Rauramaa, Rainer, Tuomilehto, Jaakko, Ingelsson, Erik, Lehtimäki, Terho, Hveem, Kristian, Palmas, Walter, März, Winfried, Kumari, Meena, Salomaa, Veikko, Chen, Yii-Der I, Rotter, Jerome I, Froguel, Philippe, Jarvelin, Marjo-Riitta, Lakatta, Edward G, Kuulasmaa, Kari, Franks, Paul W, Hamsten, Anders, Wichmann, H-Erich, Palmer, Colin N A, Stefansson, Kari, Ridker, Paul M, Loos, Ruth J F, Chakravarti, Aravinda, Deloukas, Panos, Morris, Andrew P, Newton-Cheh, Christopher, and Munroe, Patricia B
Abstract: To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure–associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure–related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
Published: 2016
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14. Genome-wide gene–environment interactions on quantitative traits using family data

Author: Sitlani, Colleen M, Dupuis, Josée, Rice, Kenneth M, Sun, Fangui, Pitsillides, Achilleas N, Cupples, L Adrienne, and Psaty, Bruce M
Abstract: Gene–environment interactions may provide a mechanism for targeting interventions to those individuals who would gain the most benefit from them. Searching for interactions agnostically on a genome-wide scale requires large sample sizes, often achieved through collaboration among multiple studies in a consortium. Family studies can contribute to consortia, but to do so they must account for correlation within families by using specialized analytic methods. In this paper, we investigate the performance of methods that account for within-family correlation, in the context of gene–environment interactions with binary exposures and quantitative outcomes. We simulate both cross-sectional and longitudinal measurements, and analyze the simulated data taking family structure into account, via generalized estimating equations (GEE) and linear mixed-effects models. With sufficient exposure prevalence and correct model specification, all methods perform well. However, when models are misspecified, mixed modeling approaches have seriously inflated type I error rates. GEE methods with robust variance estimates are less sensitive to model misspecification; however, when exposures are infrequent, GEE methods require modifications to preserve type I error rate. We illustrate the practical use of these methods by evaluating gene–drug interactions on fasting glucose levels in data from the Framingham Heart Study, a cohort that includes related individuals.
Published: 2016
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15. Strategies to Design and Analyze Targeted Sequencing Data.

Author: 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
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16. Multiethnic Genome-Wide Association Study of Cerebral White Matter Hyperintensities on MRI

Author: Verhaaren, Benjamin F.J., Debette, Stéphanie, Bis, Joshua C., Smith, Jennifer A., Ikram, M. Kamran, Adams, Hieab H., Beecham, Ashley H., Rajan, Kumar B., Lopez, Lorna M., Barral, Sandra, van Buchem, Mark A., van der Grond, Jeroen, Smith, Albert V., Hegenscheid, Katrin, Aggarwal, Neelum T., de Andrade, Mariza, Atkinson, Elizabeth J., Beekman, Marian, Beiser, Alexa S., Blanton, Susan H., Boerwinkle, Eric, Brickman, Adam M., Bryan, R. Nick, Chauhan, Ganesh, Chen, Christopher P.L.H., Chouraki, Vincent, de Craen, Anton J.M., Crivello, Fabrice, Deary, Ian J., Deelen, Joris, De Jager, Philip L., Dufouil, Carole, Elkind, Mitchell S.V., Evans, Denis A., Freudenberger, Paul, Gottesman, Rebecca F., Guðnason, Vilmundur, Habes, Mohamad, Heckbert, Susan R., Heiss, Gerardo, Hilal, Saima, Hofer, Edith, Hofman, Albert, Ibrahim-Verbaas, Carla A., Knopman, David S., Lewis, Cora E., Liao, Jiemin, Liewald, David C.M., Luciano, Michelle, van der Lugt, Aad, Martinez, Oliver O., Mayeux, Richard, Mazoyer, Bernard, Nalls, Mike, Nauck, Matthias, Niessen, Wiro J., Oostra, Ben A., Psaty, Bruce M., Rice, Kenneth M., Rotter, Jerome I., von Sarnowski, Bettina, Schmidt, Helena, Schreiner, Pamela J., Schuur, Maaike, Sidney, Stephen S., Sigurdsson, Sigurdur, Slagboom, P. Eline, Stott, David J.M., van Swieten, John C., Teumer, Alexander, Maria Töglhofer, Anna, Traylor, Matthew, Trompet, Stella, Turner, Stephen T., Tzourio, Christophe, Uh, Hae-Won, Uitterlinden, André G., Vernooij, Meike W., Wang, Jing J., Wong, Tien Y., Wardlaw, Joanna M., Windham, B. Gwen, Wittfeld, Katharina, Wolf, Christiane, Wright, Clinton B., Yang, Qiong, Zhao, Wei, Zijdenbos, Alex, Jukema, J. Wouter, Sacco, Ralph L., Kardia, Sharon L.R., Amouyel, Philippe, Mosley, Thomas H., Longstreth, W. T., DeCarli, Charles C., van Duijn, Cornelia M., Schmidt, Reinhold, Launer, Lenore J., Grabe, Hans J., Seshadri, Sudha S., Ikram, M. Arfan, and Fornage, Myriam
Published: 2015
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17. Survival is affected by mutation type and molecular mechanism in vascular Ehlers–Danlos syndrome (EDS type IV)

Author: Pepin, Melanie G., Schwarze, Ulrike, Rice, Kenneth M., Liu, Mingdong, Leistritz, Dru, and Byers, Peter H.
Abstract: Purpose:We sought to characterize the natural history of vascular Ehlers–Danlos syndrome in individuals with heterozygous COL3A1 mutations.Methods:We reviewed clinical records for details of vascular, bowel, and organ complications in 1,231 individuals (630 index cases and 601 relatives).Results:Missense and splice-site mutations accounted for more than 90% of the 572 alterations that we had identified in COL3A1. Median survival was 51 years but was influenced by gender (lower in men) and by the type of mutation.Conclusion:Although vascular Ehlers–Danlos syndrome appears to be genetically homogeneous, allelic heterogeneity is marked, and the natural history varies with gender and type of mutation in COL3A1. These findings indicate that when counseling families, confirmation of the presence of a COL3A1 mutation and its nature can help evaluate the risks of complications. These data are also important ingredients in both the selection and allocation of individuals to appropriate arms in clinical trials to assess the effects of interventions.Genet Med 16 12, 881–888.
Published: 2014
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18. Common Variation in Fatty Acid Genes and Resuscitation From Sudden Cardiac Arrest.

Author: Johnson, Catherine O., Lemaitre, Rozenn N., Fahrenbruch, Carol E., Hesselson, Stephanie, Sotoodehnia, Nona, McKnight, Barbara, Rice, Kenneth M., Pui-Yan Kwok, Siscovick, David S., and Rea, Thomas D.
Subjects: HUMAN genetic variation, FATTY acids, METABOLISM, CARDIAC arrest, VENTRICULAR fibrillation, PATIENTS
Abstract: The article presents a study which explained the relationship of genetic variation in fatty acid transport and metabolism with heart and brain resuscitation from sudden cardiac arrest (SCA). The researchers analyzed out-of-hospital SCA patients in ventricular fibrillation in King County, Washington. They found six common variants in five genes that control aspects of fatty acid metabolism which not only play important role in resuscitation but also provide potential mechanism.
Published: 2012
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19. Genomic Variation Associated With Mortality Among Adults of European and African Ancestry With Heart Failure.

Author: Morrison, Alanna C., Felix, Janine F., Cupples, L. Adrienne, Glazer, Nicole L., Loehr, Laura R., Dehghan, Abbas, Demissie, Serkalem, Bis, Joshua C., Rosamond, Wayne D., Aulchenko, Yurii S., Wang, Ying A., Haritunians, Talin, Folsom, Aaron R., Rivadeneim, Fernando, Benjamin, Emelia J., Lumley, Thomas, Couper, David, Suicker, Bruno H., O'Donnell, Christopher J., and Rice, Kenneth M.
Subjects: GENOMICS, MORTALITY, EUROPEANS, AFRICANS, HEART failure, MANAGEMENT science
Abstract: The article discusses a research study on the association of genomic variation with the mortality of European adults and those with African ancestry caused by heart failure (HF). Subjects include 466 persons with African ancestry who have had HF incidents and 2,526 of those with European ancestry who have HF based on the Cox proportional hazard models with adjustments regarding sex and the time of the HF event. Results indicate the identification of new locus related to all-cause mortality of those with European ancestry who had HF experiences.
Published: 2010
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20. Short-term and long-term risk of incident ischemic stroke after transient ischemic attack.

Author: Thacker EL, Wiggins KL, Rice KM, Longstreth WT Jr, Bis JC, Dublin S, Smith NL, Heckbert SR, Psaty BM, Thacker, Evan L, Wiggins, Kerri L, Rice, Kenneth M, Longstreth, W T Jr, Bis, Joshua C, Dublin, Sascha, Smith, Nicholas L, Heckbert, Susan R, and Psaty, Bruce M
Published: 2010
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21. Genetic variation in angiotensin-converting enzyme-related pathways associated with sudden cardiac arrest risk.

Author: Sotoodehnia N, Li G, Johnson CO, Lemaitre RN, Rice KM, Rea TD, Siscovick DS, Sotoodehnia, Nona, Li, Guo, Johnson, Catherine O, Lemaitre, Rozenn N, Rice, Kenneth M, Rea, Thomas D, and Siscovick, David S
Abstract: Background: Angiotensin-converting enzyme (ACE)-related pathways influence arrhythmias and sudden cardiac arrest (SCA) risk.Objective: The purpose of this study was to investigate whether genetic variations in ACE-related pathways are associated with SCA risk. Because these pathways are sex dependent and are influenced by estrogen, we examined these genotype-SCA associations in the full study population and tested for interaction with gender.Methods: In a population-based case-control study set in King County, Washington, 211 SCA cases (80% male; mean age 59 years,) and 730 age- and gender-matched controls of European descent were genotyped for 47 single nucleotide polymorphisms (SNPs) in eight genes (ACE, AGT, REN, AGTR1, AGTR2, ACE2, KNG1, BDKRB2). The association of SNPs and haplotypes with SCA risk was examined using logistic regression.Results: AGTR1 SNP rs1492099 (allele frequency 15%) was associated with decreased SCA risk (odds ratio [OR] 0.62, 95% confidence interval [CI] 0.4-0.9). Haplotype variation in AGTR2 was associated with SCA risk (global haplotype test P = .001), with haplotype 2 (allele frequency 27%) associated with increased risk (OR 1.26, 95% CI 1.1-1.5). There was interaction with gender on SCA risk for variation in KNG1 (interaction P value range 0.0004-0.017 for 6/8 SNPs). KNG1 SNP rs710448 (allele frequency 42%) was associated with decreased risk (OR 0.44, 95% CI 0.3-0.8) among women but not men. Other SNPs and haplotypes in the eight genes examined were not associated with SCA risk after multiple testing correction.Conclusion: Variations in AGTR1 and AGTR2 are associated with SCA risk in a population-based case-control study. There was evidence of interaction with gender on SCA risk for variation in KNG1. These study findings, if replicated, suggest that variation in genes in ACE-related pathways influence SCA risk. [ABSTRACT FROM AUTHOR]
Published: 2009
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22. Genetic variation in angiotensin-converting enzyme–related pathways associated with sudden cardiac arrest risk.

Author: Sotoodehnia, Nona, Li, Guo, Johnson, Catherine O., Lemaitre, Rozenn N., Rice, Kenneth M., Rea, Thomas D., and Siscovick, David S.
Abstract: Background: Angiotensin-converting enzyme (ACE)–related pathways influence arrhythmias and sudden cardiac arrest (SCA) risk. Objective: The purpose of this study was to investigate whether genetic variations in ACE-related pathways are associated with SCA risk. Because these pathways are sex dependent and are influenced by estrogen, we examined these genotype–SCA associations in the full study population and tested for interaction with gender. Methods: In a population-based case-control study set in King County, Washington, 211 SCA cases (80% male; mean age 59 years,) and 730 age- and gender-matched controls of European descent were genotyped for 47 single nucleotide polymorphisms (SNPs) in eight genes (ACE, AGT, REN, AGTR1, AGTR2, ACE2, KNG1, BDKRB2). The association of SNPs and haplotypes with SCA risk was examined using logistic regression. Results: AGTR1 SNP rs1492099 (allele frequency 15%) was associated with decreased SCA risk (odds ratio [OR] 0.62, 95% confidence interval [CI] 0.4–0.9). Haplotype variation in AGTR2 was associated with SCA risk (global haplotype test P = .001), with haplotype 2 (allele frequency 27%) associated with increased risk (OR 1.26, 95% CI 1.1–1.5). There was interaction with gender on SCA risk for variation in KNG1 (interaction P value range 0.0004–0.017 for 6/8 SNPs). KNG1 SNP rs710448 (allele frequency 42%) was associated with decreased risk (OR 0.44, 95% CI 0.3–0.8) among women but not men. Other SNPs and haplotypes in the eight genes examined were not associated with SCA risk after multiple testing correction. Conclusion: Variations in AGTR1 and AGTR2 are associated with SCA risk in a population-based case-control study. There was evidence of interaction with gender on SCA risk for variation in KNG1. These study findings, if replicated, suggest that variation in genes in ACE-related pathways influence SCA risk. [Copyright &y& Elsevier]
Published: 2009
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23. Red blood cell membrane α-linolenic acid and the risk of sudden cardiac arrest.

Author: Lemaitre, Rozenn N., King, Irena B., Sotoodehnia, Nona, Rea, Thomas D., Raghunathan, Trivellore E., Rice, Kenneth M., Lumley, Thomas S., Knopp, Robert H., Cobb, Leonard A., Copass, Michael K., and Siscovick, David S.
Subjects: ERYTHROCYTES, CELL membranes, LINOLENIC acids, CARDIAC arrest, UNSATURATED fatty acids, DISEASE risk factors, CASE-control method
Abstract: Abstract: Higher levels of long-chain n-3 polyunsaturated fatty acids in red blood cell membranes are associated with lower risk of sudden cardiac arrest. Whether membrane levels of α-linolenic acid, a medium-chain n-3 polyunsaturated fatty acid, show a similar association is unclear. We investigated the association of red blood cell membrane α-linolenic acid with sudden cardiac arrest risk in a population-based case-control study. Cases, aged 25 to 74 years, were out-of-hospital sudden cardiac arrest patients attended by paramedics in Seattle, WA (n = 265). Controls, matched to cases by age, sex, and calendar year, were randomly identified from the community (n = 415). All participants were free of prior clinically diagnosed heart disease. Blood was obtained at the time of cardiac arrest (cases) or at the time of an interview (controls). Higher membrane α-linolenic acid was associated with a higher risk of sudden cardiac arrest: after adjustment for matching factors and smoking, diabetes, hypertension, education, physical activity, weight, height, and total fat intake, the odds ratios corresponding to increasing quartiles of α-linolenic acid were 1.7 (95% confidence interval [CI], 1.0-3.0), 1.9 (95% CI, 1.1-3.3), and 2.5 (95% CI, 1.3-4.8) compared with the lowest quartile. The association was independent of red blood cell levels of long-chain n-3 fatty acids, trans-fatty acids, and linoleic acid. Higher membrane levels of α-linolenic acid are associated with higher risk of sudden cardiac arrest. [Copyright &y& Elsevier]
Published: 2009
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24. Strategies to Design and Analyze Targeted Sequencing Data

Author: 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
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25. Lower Risk of Cardiovascular Events in Postmenopausal Women Taking Oral Estradiol Compared With Oral Conjugated Equine Estrogens

Author: Smith, Nicholas L., Blondon, Marc, Wiggins, Kerri L., Harrington, Laura B., van Hylckama Vlieg, Astrid, Floyd, James S., Hwang, Melody, Bis, Joshua C., McKnight, Barbara, Rice, Kenneth M., Lumley, Thomas, Rosendaal, Frits R., Heckbert, Susan R., and Psaty, Bruce M.
Abstract: IMPORTANCE Little is known about the comparative cardiovascular safety of oral hormone therapy products, which impedes women from making informed safety decisions about hormone therapy to treat menopausal symptoms. OBJECTIVE To compare the relative clinical cardiovascular safety of 2 commonly used oral estrogen drugs—conjugated equine estrogens (CEEs) and estradiol. DESIGN, SETTING, AND PARTICIPANTS Population-based, case-control study from January 1, 2003, to December 31, 2009, comparing cardiovascular event risk associated with current CEEs and estradiol use in a large health maintenance organization in which the preferred formulary estrogen changed from CEEs to estradiol during the course of data collection. Participants were 384 postmenopausal women aged 30 to 79 years using oral hormone therapy. MAIN OUTCOMES AND MEASURES Incident venous thrombosis was the primary clinical outcome, and incident myocardial infarction and ischemic stroke were secondary outcomes. As validation, an intermediate clotting phenotype, the endogenous thrombin potential–based normalized activated protein C sensitivity ratio, was measured in plasma of controls. RESULTS We studied 68 venous thrombosis, 67 myocardial infarction, and 48 ischemic stroke cases, with 201 matched controls; all participants were current users of oral CEEs or estradiol. In adjusted analyses, current oral CEEs use compared with current oral estradiol use was associated with an increased venous thrombosis risk (odds ratio, 2.08; 95% CI, 1.02-4.27; P = .045) and an increased myocardial infarction risk that did not reach statistical significance (odds ratio, 1.87; 95% CI, 0.91-3.84; P = .09) and was not associated with ischemic stroke risk (odds ratio, 1.13; 95% CI, 0.55-2.31; P = .74). Among 140 controls, CEEs users compared with estradiol users had higher endogenous thrombin potential–based normalized activated protein C sensitivity ratios (P < .001), indicating a stronger clotting propensity. CONCLUSIONS AND RELEVANCE In an observational study of oral hormone therapy users, CEEs use was associated with a higher risk of incident venous thrombosis and possibly myocardial infarction than estradiol use. This risk differential was supported by biologic data. These findings need replication and suggest that various oral estrogen drugs may be associated with different levels of cardiovascular risk.
Published: 2014
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26. The association of smoking with venous thrombosis in women

Author: Blondon, Marc, Wiggins, Kerri L., McKnight, Barbara, Psaty, Bruce M., Rice, Kenneth M., Heckbert, Susan R., and Smith, Nicholas L.
Published: 2013
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27. Common Variation in Fatty Acid Genes and Resuscitation From Sudden Cardiac Arrest

Author: Johnson, Catherine O., Lemaitre, Rozenn N., Fahrenbruch, Carol E., Hesselson, Stephanie, Sotoodehnia, Nona, McKnight, Barbara, Rice, Kenneth M., Kwok, Pui-Yan, Siscovick, David S., and Rea, Thomas D.
Abstract: Fatty acids provide energy and structural substrates for the heart and brain and may influence resuscitation from sudden cardiac arrest (SCA). We investigated whether genetic variation in fatty acid metabolism pathways was associated with SCA survival.
Published: 2012
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28. Genetic variation associated with plasma von Willebrand factor levels and the risk of incident venous thrombosis

Author: Smith, Nicholas L., Rice, Kenneth M., Bovill, Edwin G., Cushman, Mary, Bis, Joshua C., McKnight, Barbara, Lumley, Thomas, Glazer, Nicole L., van Hylckama Vlieg, Astrid, Tang, Weihong, Dehghan, Abbas, Strachan, David P., O'Donnell, Christopher J., Rotter, Jerome I., Heckbert, Susan R., Psaty, Bruce M., and Rosendaal, Frits R.
Abstract: In a recent genome-wide association study, variants in 8 genes were associated with VWF level, a risk factor for venous thrombosis (VT). In an independent, population-based, case-control study of incident VT, we tested hypotheses that variants in these genes would be associated with risk. Cases were 656 women who experienced an incident VT, and controls comprised 710 women without a history of VT. DNA was obtained from whole blood. Logistic regression was used to test associations between incident VT and single nucleotide polymorphisms (SNPs) in 7 genes not previously shown to be associated with VT. Associations with P < .05 were candidates for replication in an independent case-control study of VT in both sexes. Two of the 7 SNPs tested yielded P < .05: rs1039084 (P = .005) in STXBP5, a novel candidate gene for VT, and rs1063856 (P = .04) in VWF, a gene whose protein level is associated with VT risk. Association results for the remaining 5 variants in SCARA5, STAB2, STX2, TC2N, and CLEC4M were not significant. Both STXBP5 and VWF findings were replicated successfully. Variation in genes associated with VWF levels in the genome-wide association study was found to be independently associated with incident VT.
Published: 2011
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29. Genetic variation associated with plasma von Willebrand factor levels and the risk of incident venous thrombosis

Author: Smith, Nicholas L., Rice, Kenneth M., Bovill, Edwin G., Cushman, Mary, Bis, Joshua C., McKnight, Barbara, Lumley, Thomas, Glazer, Nicole L., van Hylckama Vlieg, Astrid, Tang, Weihong, Dehghan, Abbas, Strachan, David P., O'Donnell, Christopher J., Rotter, Jerome I., Heckbert, Susan R., Psaty, Bruce M., and Rosendaal, Frits R.
Abstract: In a recent genome-wide association study, variants in 8 genes were associated with VWF level, a risk factor for venous thrombosis (VT). In an independent, population-based, case-control study of incident VT, we tested hypotheses that variants in these genes would be associated with risk. Cases were 656 women who experienced an incident VT, and controls comprised 710 women without a history of VT. DNA was obtained from whole blood. Logistic regression was used to test associations between incident VT and single nucleotide polymorphisms (SNPs) in 7 genes not previously shown to be associated with VT. Associations with P< .05 were candidates for replication in an independent case-control study of VT in both sexes. Two of the 7 SNPs tested yielded P< .05: rs1039084 (P= .005) in STXBP5, a novel candidate gene for VT, and rs1063856 (P= .04) in VWF, a gene whose protein level is associated with VT risk. Association results for the remaining 5 variants in SCARA5, STAB2, STX2, TC2N, and CLEC4Mwere not significant. Both STXBP5and VWFfindings were replicated successfully. Variation in genes associated with VWF levels in the genome-wide association study was found to be independently associated with incident VT.
Published: 2011
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30. Genomic Variation Associated With Mortality Among Adults of European and African Ancestry With Heart Failure

Author: Morrison, Alanna C., Felix, Janine F., Cupples, L. Adrienne, Glazer, Nicole L., Loehr, Laura R., Dehghan, Abbas, Demissie, Serkalem, Bis, Joshua C., Rosamond, Wayne D., Aulchenko, Yurii S., Wang, Ying A., Haritunians, Talin, Folsom, Aaron R., Rivadeneira, Fernando, Benjamin, Emelia J., Lumley, Thomas, Couper, David, Stricker, Bruno H., O’Donnell, Christopher J., Rice, Kenneth M., Chang, Patricia P., Hofman, Albert, Levy, Daniel, Rotter, Jerome I., Fox, Ervin R., Uitterlinden, Andre G., Wang, Thomas J., Psaty, Bruce M., Willerson, James T., van Duijn, Cornelia M., Boerwinkle, Eric, Witteman, Jacqueline C.M., Vasan, Ramachandran S., and Smith, Nicholas L.
Abstract: Prognosis and survival are significant concerns for individuals with heart failure (HF). To better understand the pathophysiology of HF prognosis, the association between 2 366 858 single-nucleotide polymorphisms (SNPs) and all-cause mortality was evaluated among individuals with incident HF from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.
Published: 2010
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31. Association of Genome-Wide Variation With the Risk of Incident Heart Failure in Adults of European and African Ancestry

Author: Smith, Nicholas L., Felix, Janine F., Morrison, Alanna C., Demissie, Serkalem, Glazer, Nicole L., Loehr, Laura R., Cupples, L. Adrienne, Dehghan, Abbas, Lumley, Thomas, Rosamond, Wayne D., Lieb, Wolfgang, Rivadeneira, Fernando, Bis, Joshua C., Folsom, Aaron R., Benjamin, Emelia, Aulchenko, Yurii S., Haritunians, Talin, Couper, David, Murabito, Joanne, Wang, Ying A., Stricker, Bruno H., Gottdiener, John S., Chang, Patricia P., Wang, Thomas J., Rice, Kenneth M., Hofman, Albert, Heckbert, Susan R., Fox, Ervin R., O’Donnell, Christopher J., Uitterlinden, Andre G., Rotter, Jerome I., Willerson, James T., Levy, Daniel, van Duijn, Cornelia M., Psaty, Bruce M., Witteman, Jacqueline C.M., Boerwinkle, Eric, and Vasan, Ramachandran S.
Abstract: Although genetic factors contribute to the onset of heart failure (HF), no large-scale genome-wide investigation of HF risk has been published to date. We have investigated the association of 2 478 304 single-nucleotide polymorphisms with incident HF by meta-analyzing data from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.
Published: 2010
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32. Short-Term and Long-Term Risk of Incident Ischemic Stroke After Transient Ischemic Attack

Author: Thacker, Evan L., Wiggins, Kerri L., Rice, Kenneth M., Longstreth, W T., Bis, Joshua C., Dublin, Sascha, Smith, Nicholas L., Heckbert, Susan R., and Psaty, Bruce M.
Abstract: The relative risk of ischemic stroke associated with transient ischemic attack (TIA) is not well defined because most studies of stroke after TIA did not include comparison groups. We sought to estimate short-term and long-term relative risks of ischemic stroke associated with clinically diagnosed TIA.
Published: 2010
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33. Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.

Author: Gorski, Mathias, Rasheed, Humaira, Teumer, Alexander, Thomas, Laurent F., Graham, Sarah E., Sveinbjornsson, Gardar, Winkler, Thomas W., Günther, Felix, Stark, Klaus J., Chai, Jin-Fang, Tayo, Bamidele O., Wuttke, Matthias, Li, Yong, Tin, Adrienne, Ahluwalia, Tarunveer S., Ärnlöv, Johan, Åsvold, Bjørn Olav, Bakker, Stephan J.L., Banas, Bernhard, Bansal, Nisha, Biggs, Mary L., Biino, Ginevra, Böhnke, Michael, Boerwinkle, Eric, Bottinger, Erwin P., Brenner, Hermann, Brumpton, Ben, Carroll, Robert J., Chaker, Layal, Chalmers, John, Chee, Miao-Li, Chee, Miao-Ling, Cheng, Ching-Yu, Chu, Audrey Y., Ciullo, Marina, Cocca, Massimiliano, Cook, James P., Coresh, Josef, Cusi, Daniele, de Borst, Martin H., Degenhardt, Frauke, Eckardt, Kai-Uwe, Endlich, Karlhans, Evans, Michele K., Feitosa, Mary F., Franke, Andre, Freitag-Wolf, Sandra, Fuchsberger, Christian, Gampawar, Piyush, Gansevoort, Ron T., Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Gieger, Christian, Gudbjartsson, Daniel F., Hallan, Stein, Hamet, Pavel, Hishida, Asahi, Ho, Kevin, Hofer, Edith, Holleczek, Bernd, Holm, Hilma, Hoppmann, Anselm, Horn, Katrin, Hutri-Kähönen, Nina, Hveem, Kristian, Hwang, Shih-Jen, Ikram, M. Arfan, Josyula, Navya Shilpa, Jung, Bettina, Kähönen, Mika, Karabegović, Irma, Khor, Chiea-Chuen, Koenig, Wolfgang, Kramer, Holly, Krämer, Bernhard K., Kühnel, Brigitte, Kuusisto, Johanna, Laakso, Markku, Lange, Leslie A., Lehtimäki, Terho, Li, Man, Lieb, Wolfgang, Lind, Lars, Lindgren, Cecilia M., Loos, Ruth J.F., Lukas, Mary Ann, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Matias-Garcia, Pamela R., Meisinger, Christa, Meitinger, Thomas, Melander, Olle, Milaneschi, Yuri, Mishra, Pashupati P., Mononen, Nina, Morris, Andrew P., Mychaleckyj, Josyf C., Nadkarni, Girish N., Naito, Mariko, Nakatochi, Masahiro, Nalls, Mike A., Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, Ilja M., Nutile, Teresa, O’Donoghue, Michelle L., O'Connell, Jeffrey, Olafsson, Isleifur, Orho-Melander, Marju, Parsa, Afshin, Pendergrass, Sarah A., Penninx, Brenda W.J. H., Pirastu, Mario, Preuss, Michael H., Psaty, Bruce M., Raffield, Laura M., Raitakari, Olli T., Rheinberger, Myriam, Rice, Kenneth M., Rizzi, Federica, Rosenkranz, Alexander R., Rossing, Peter, Rotter, Jerome I., Ruggiero, Daniela, Ryan, Kathleen A., Sabanayagam, Charumathi, Salvi, Erika, Schmidt, Helena, Schmidt, Reinhold, Scholz, Markus, Schöttker, Ben, Schulz, Christina-Alexandra, Sedaghat, Sanaz, Shaffer, Christian M., Sieber, Karsten B., Sim, Xueling, Sims, Mario, Snieder, Harold, Stanzick, Kira J., Thorsteinsdottir, Unnur, Stocker, Hannah, Strauch, Konstantin, Stringham, Heather M., Sulem, Patrick, Szymczak, Silke, Taylor, Kent D., Thio, Chris H.L., Tremblay, Johanne, Vaccargiu, Simona, van der Harst, Pim, van der Most, Peter J., Verweij, Niek, Völker, Uwe, Wakai, Kenji, Waldenberger, Melanie, Wallentin, Lars, Wallner, Stefan, Wang, Judy, Waterworth, Dawn M., White, Harvey D., Willer, Cristen J., Wong, Tien-Yin, Woodward, Mark, Yang, Qiong, Yerges-Armstrong, Laura M., Zimmermann, Martina, Zonderman, Alan B., Bergler, Tobias, Stefansson, Kari, Böger, Carsten A., Pattaro, Cristian, Köttgen, Anna, Kronenberg, Florian, and Heid, Iris M.
Abstract: Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silicoevidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.
Published: 2022
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34. Effect of progestogen and progestogen type on hemostasis measures in postmenopausal women

Author: Smith, Nicholas L., Wiley, Jennifer R., Legault, Claudine, Rice, Kenneth M., Heckbert, Susan R., Psaty, Bruce M., Tracy, Russell P., and Cushman, Mary
Abstract: The contribution of progestogen therapy or progestogen type to risks and benefits of estrogen treatment is inadequately characterized. We examined the effect of conjugated equine estrogens (CEE) with and without concomitant progestogen treatments on changes in hemostasis measures among Postmenopausal Estrogen/Progestin Intervention participants.
Published: 2008
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35. Common genetic variation in six lipid-related and statin-related genes, statin use and risk of incident nonfatal myocardial infarction and stroke

Author: Hindorff, Lucia A., Lemaitre, Rozenn N., Smith, Nicholas L., Bis, Joshua C., Marciante, Kristin D., Rice, Kenneth M., Lumley, Thomas, Enquobahrie, Daniel A., Li, Guo, Heckbert, Susan R., and Psaty, Bruce M.
Abstract: Genetic polymorphisms are associated with lipid-lowering response to statins, but generalizeability to disease endpoints is unclear. The association between 82 common single nucleotide polymorphisms (SNPs) in six lipid-related or statin-related genes (ABCB1, CETP, HMGCR, LDLR, LIPC, NOS3) and incident nonfatal myocardial infarction (MI) and ischemic stroke was analyzed according to current statin use and overall in a population-based case–control study (856 MI, 368 stroke, 2686 controls).
Published: 2008
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36. Common variation in cytochrome P450 epoxygenase genes and the risk of incident nonfatal myocardial infarction and ischemic stroke

Author: Marciante, Kristin D., Totah, Rheem A., Heckbert, Susan R., Smith, Nicholas L., Lemaitre, Rozenn N., Lumley, Thomas, Rice, Kenneth M., Hindorff, Lucia A., Bis, Joshua C., Hartman, Brittany, and Psaty, Bruce M.
Abstract: The biologically active epoxyeicosatrienoic acids have protective vascular effects. CYP2J2, CYP2C8, and CYP2C9 are known to be a source of epoxyeicosatrienoic acids in cardiac tissues. We conducted a population-based, case–control study at Group Health to determine whether common genetic variation in the CYP2J2, CYP2C8, and CYP2C9genes was associated with the risk of myocardial infarction and ischemic stroke.
Published: 2008
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37. Myocardial infarction and stroke associated with diuretic based two drug antihypertensive regimens: population based case-control study

Author: Boger-Megiddo, Inbal, Heckbert, Susan R, Weiss, Noel S, McKnight, Barbara, Furberg, Curt D, Wiggins, Kerri L, Delaney, Joseph A C, Siscovick, David S, Larson, Eric B, Lemaitre, Rozenn N, Smith, Nicholas L, Rice, Kenneth M, Glazer, Nicole L, and Psaty, Bruce M
Abstract: OBJECTIVE: To examine the association of myocardial infarction and stroke incidence with several commonly used two drug antihypertensive treatment regimens. Design Population based case-control study. Setting Group Health Cooperative, Seattle, WA, USA. Participants Cases (n=353) were aged 30-79 years, had pharmacologically treated hypertension, and were diagnosed with a first fatal or non-fatal myocardial infarction or stroke between 1989 and 2005. Controls (n=952) were a random sample of Group Health members who had pharmacologically treated hypertension. We excluded individuals with heart failure, evidence of coronary heart disease, diabetes, or chronic kidney disease. Exposures One of three common two drug combinations: diuretics plus β blockers; diuretics plus calcium channel blockers; and diuretics plus angiotensin converting enzyme inhibitors or angiotensin receptor blockers. MAIN OUTCOME MEASURES: Myocardial infarction or stroke. RESULTS: Compared with users of diuretics plus β blockers, users of diuretics plus calcium channel blockers had an increased risk of myocardial infarction (adjusted odds ratio (OR) 1.98, 95% confidence interval 1.37 to 2.87) but not of stroke (OR 1.02, 95% CI 0.63 to 1.64). The risks of myocardial infarction and stroke in users of diuretics plus angiotensin converting enzyme inhibitors or angiotensin receptor blockers were slightly but not significantly lower than in users of diuretics plus β blockers (myocardial infarction: OR 0.76, 95% CI 0.52 to 1.11; stroke: OR 0.71, 95% CI 0.46 to 1.10). CONCLUSIONS: In patients with hypertension, diuretics plus calcium channel blockers were associated with a higher risk of myocardial infarction than other common two drug treatment regimens. A large trial of second line antihypertensive treatments in patients already on low dose diuretics is required to provide a solid basis for treatment recommendations.
Published: 2010

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